• Journal of Preventive Medicine and Public Health
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• v.51 no.3
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• pp.163-168
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• 2018

Objectives: Due to their developmental characteristics, adolescents have a higher probability than other age groups of experiencing injuries caused by accidents, violence, and intentional self-harm. The severity and characteristics of injuries vary by the intentionality and mechanism of injury; therefore, there is a need for a national-level estimate of the scale and the severity of injuries in adolescents that takes these factors into account. Methods: By using data from the Emergency Department-based Injury In-depth Surveillance Data, National Emergency Department Information System, the Korean National Hospital Discharge In-depth Injury Survey, and cause of death statistics, we calculated the emergency department (ED) visit rate, hospitalization rate, and death rate of injuries per 100 000 adolescents for each injury mechanism. The calculated rates were used to generate the injury pyramid ratio (ratio of death rate to hospitalization rate to ED visit rate) to visualize the scale and the severity of the injury. Results: The mortality rate in adolescents due to injury was 10/100 000; the corresponding rates for hospitalization and ED visits were 1623 and 4923, respectively, resulting in an injury pyramid ratio with the general pyramid form, with a 1:162:492 ratio of deaths to hospitalizations to ED visits. The mortality rate due to suicide/intentional self-harm was 5/100 000, while 35 were hospitalized for this reason and 74 made ED visits. The pyramid ratio of 1:7:15 for intentional self-harm/suicide showed a steep pyramidal form, indicating considerable lethality. The mortality rate due to motor vehicle collisions (MVCs) was 3/100 000; 586 were hospitalized for this reason, while 1023 made ED visits. The pyramid ratio of 1:195:341 for MVCs showed a gradual pyramid form, indicating that the lethality was low and the scale of injury was high. Conclusions: The main categories of injuries in adolescents were visualized in pyramid form, contributing to an understanding of the scale of each injury by mechanism in terms of levels of death, hospitalization, and ED visits. These findings will be helpful for understanding how to prioritize injuries in adolescents.

• Korea journal of population studies
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• v.26 no.2
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• pp.1-32
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• 2003

An analysis on cause-specific mortality at the provincial level provides essential information for policy formulation and makes it possible to draw hypotheses regarding various diseases and causes of death. Although the mortality level and causes of death at the provincial level are determined by the multiple effects of socioeconomic, cultural, medical and ecological factors, this study primarily intends to examine similarities and differences of cause-specific mortality at the provincial level. Utilizing the registered death and the registered population as of 1998, the delayed death registration and unreported infant deaths were supplemented at the provincial level and age-standardized death rates and life tables were calculated. Regarding the mortality level due to all causes, major findings were as follow: (1) For both sexes as a whole, Seoul showed the lowest mortality level, and Jeonnam showed the highest mortality level; and (2) The differences of the mortality level among provinces were greater for males than females and for those less than 65 years than those 65 years and over. Regarding the cause-specific mortality level revealed in all indicators (cause-specific age-standardized mortality rates and the probability of dying at birth due to a specific cause for males, females, and both sexes combined respectively), the major findings were as follow: (1) The mortality level due to heart diseases was the highest in Busan and the lowest in Gangweon; (2) The mortality level due to liver diseases was the highest in Chonnam; and (3) The mortality level due to traffic accidents was the highest in Chungnam and the lowest in Inchon. As the mortality differentials at the provincial level are related to various factors, exploratory statistical analysis is attempted for the 25 explanatory variables including socioeconomic variables and 90 mortality variables. Mortality due to all causes are related to socioeconomic variables. Among cause-specific mortality, mortality due to liver diseases and traffic accidents is related to socioeconomic variables. Finally, the need to improve the quality of death certificate is discussed.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9453-9458
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• 2014

Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.6D
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• pp.577-585
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• 2010

Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2259-2263
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• 2013

Background: Public use National Health and Nutrition Examination Survey (NHANES III) and NHANES III linked mortality data were here applied to investigate the association between health insurance coverage and all cause and all cancer mortality in adults. Patients and Methods: NHANES III household adult, laboratory and mortality data were merged. Only patients examined in the mobile examination center (MEC) were included in this study. The sampling weight employed was WTPFEX6, SDPPSU6 being used for the probability sampling unit and SDPSTRA6 to designate the strata for the survey analysis. All cause and all cancer mortalities were used as binary outcomes. The effect of health insurance coverage status on all cause and all cancer mortalities were analyzed with potential socioeconomic, behavioral and health status confounders. Results: There were 2398 sample persons included in this study. The mean age was 40 years and the mean (S.E.) follow up was 171.85 (3.12) person months from the MEC examination. For all cause mortality, the odds ratios (significant p-values) of the covariates were: age, 1.0095 (0.000); no health insurance coverage (using subjects with health insurance), 1.71 (0.092); black race (using non-Hispanic white subjects as the reference group) 1.43, (0.083); Mexican-Americans, 0.60 (0.089); DMPPIR, 0.82, (0.000); and drinking hard liquor, 1.014 (0.007). For all cancer mortality, the odds ratio (significant p-values) of the covariates were: age, 1.0072 (0.00); no health insurance coverage, using with health coverage as the reference group, 2.91 (0.002); black race, using non-Hispanic whites as the reference group, 1.64 (0.047); Mexican Americans, 0.33 (0.008) and smoking, 1.017 (0.118). Conclusion: There was a 70% increase in risk of all cause death and almost 300% of all cancer death for people without any health insurance coverage.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.11
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• pp.5525-5528
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• 2012

Introduction: Breast cancer is the most common cancer in women. Improvements of early diagnosis modalities have led to longer survival rates. This study aimed to determine the 5, 10 and 15 year mortality rates of breast cancer patients compared to the normal female population. Materials and Methods: The follow up data of a cohort of 615 breast cancer patients referred to Iranian Breast Cancer Research Center (BCRC) from 1986 to 1996 was considered as reference breast cancer dataset. The dataset was divided into 5 year age groups and the 5, 10 and 15 year probability of death for each group was estimated. The annual mortality rate of Iranian women was obtained from the Death Registry system. Standardized mortality ratios (SMRs) of breast cancer patients were calculated using the ratio of the mortality rate in breast cancer patients over the general female population. Results: The mean age of breast cancer patients at diagnosis time was 45.9 (${\pm}10.5$) years ranging from 24-74. A total of 73, 32 and 2 deaths were recorded at 5, 10 and 15 years, respectively, after diagnosis. The SMRs for breast cancer patients at 5, 10 and 15 year intervals after diagnosis were 6.74 (95% CI, 5.5-8.2), 6.55 (95%CI, 5-8.1) and 1.26 (95%CI, 0.65-2.9), respectively. Conclusion: Results showed that the observed mortality rate of breast cancer patients after 15 years from diagnosis was very similar to expected rates in general female population. This finding would be useful for clinicians and health policy makers to adopt a beneficial strategy to improve breast cancer survival. Further follow-up time with larger sample size and a pooled analysis of survival rates of different centres may shed more light on mortality patterns of breast cancer.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1311-1327
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• 2016

We propose a multi-state model for analyzing semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the 'illness-death model', which composes three states, such as 'healthy', 'diseased', and 'dead'. The state of 'diseased' can be considered as an intermediate event. Two more states are added into the illness-death model to describe missing events caused by a loss of follow-up before the end of the study. One of them is a state of 'LTF', representing a lost-to-follow-up, and the other is an unobservable state that represents the intermediate event experienced after LTF occurred. Given covariates, we employ the Cox proportional hazards model with a normal frailty and construct a full likelihood to estimate transition intensities between states in the multi-state model. Marginalization of the full likelihood is completed using the adaptive Gaussian quadrature, and the optimal solution of the regression parameters is achieved through the iterative Newton-Raphson algorithm. Simulation studies are carried out to investigate the finite-sample performance of the proposed estimation procedure in terms of the empirical coverage probability of the true regression parameter. Our proposed method is also illustrated with the dataset adapted from Helmer et al. (2001).

• Journal of Chest Surgery
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• v.20 no.1
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• pp.48-54
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• 1987

This report provides follow-up data on 557 patients [73 aortic, 357 mitral, and 127 multiple valve replacements] undergone lonescu-Shiley pericardial Xenograft valve replacement at Seoul National University Hospital between January, 1979 and December, 1985. There were 35 early death [6.3%] and 522 operative survivors were observed, and the cumulative follow-up is 1,140 patient-years [mean: 2.18 years per patient] The thromboembolic complications occurred in 34 cases [3.0% per patient-year] and the rate was 2.1% per patient-year for mitral and 0.3% per patient-year for aortic valve replacement in the presence of anticoagulation therapy. Among the 34 embolic episodes, 9 patients were dead [0.8% per patient-year] and the cause of death were 5 cerebral thromboembolism, 2 pulmonary embolism, and 2 intracerebral hemorrhage due to inappropriate anticoagulation after thromboembolic episode. Actuarial probability [+ SEM] of remaining free of thromboembolism for AVR is 88.1 x 11.1% at 5 years, for MVR 79.1 a 13.4% at 7 years and for multiple valve replacement 77.2 e 5.21% at 7 years. The incidence rate of thromboembolic complications after AVR is not less than that of MVR [0.3 Among the potential thromboembolic risk factors, atrial fibrillation is possible risk factor to increase the thromboembolic complication [0.05 < P < 0.1], but the importance of other factors, such as atrial clot, large left atrial size, mitral position, NYHA functional class, and age is less definite. A careful follow-up and the proper control of anticoagulation without omission, poor control, and arbitrary withdrawal is important for the successful management of the thromboembolic complications and the anticoagulation-related morbidity and mortality.

• Journal of Chest Surgery
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• v.20 no.1
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• pp.13-21
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• 1987

To clarify the difference between the outcome of warfarin anticoagulation and the antiplatelet [Aspirin, Dipyridamole] therapy after bioprosthetic heart valve replacement, we compared the following two groups. Group I [Warfarin group] consisted of 557 patients undergone lonescu - Shiley valve replacement between January, 1979 and December, 1985, and treated with scheduled warfarin therapy at Seoul National University Hospital. Group II [Antiplatelet group] consisted of 128 patients undergone lonescu - Shiley, Carpentier - Edwards or Wessex bioprosthetic valve replacement between March, 1983 and December, 1986, and treated primarily with antiplatelet therapy [Aspirin plus Dipyridamole] at SeJong General Hospital. The two groups were similar with respect to age, number of valves utilized per patient, type of operation and risk factors of thromboembolism. In group I, 522 patients excluding 35 hospital death [hospital mortality 6.3%], and in group II, 119 survivors excluding 9 hospital death [hospital mortality 7.0%] were followed. In group I, there were 13 fatal complications, of which seven were thromboembolic [0.6% / pt-yr] and six hemorrhagic [0.5%/pt-yr] during the period of four years. In group II, there were 3 fatal thromboembolic complications [2.3%/pt-yr] during the period of four years. This showed no statistically significant difference. Apart from fatal complications, there were lots of warfarin related minor complications in group I comparing with those of group II. The actuarial probability of the freedom from thromboembolism and of the freedom from fatal complications were very similar at each corresponding years postoperatively. As a result, warfarin anticoagulation in patients with bioprosthetic valve replacement did not reveal any significant advantages over antiplatelet therapy.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.145-157
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• 2018

In this study, we analyzed the effect of the income level of cancer, stroke, and myocardial infarction on mortality by using National Health Insurance Service(NHIS) Cohort 2.0 DB. Patients who newly developed the disease in 2007 were observed till 2015. The analysis used the Cox probability proportional risk model and the competing risk model. The income level used information at the time of the onset of the disease in 2007, categorized into low / mid / high. The results showed that there were differences in the risks of death and secondary disease in patients with cancer, stroke, or myocardial infarction according to the income level. In addition to the need for a social safety net to lower the incidence of early deaths in low-income families, it seems necessary to continue to strengthen universal protection for serious diseases similar to the current policy.