• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.77-96
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• 2018

A reverse mortgage provides a pension until the death for the insured or last survivor. Long-term risk management is important to estimate the contractual period of a reverse mortgage. It is also necessary to study prediction methods of mortality rates that appropriately reflect the improvement trend of the mortality rate since the extension of the life expectancy, which is the main cause of aging, can have a serious impact on the pension financial soundness. In this study, the Lee-Carter (LC) model reflects the improvement in mortality rates; in addition, multiple life model are also applied to a reverse mortgage. The mortality prediction method by the traditional LC model has shown a dramatic improvement in the mortality rate; therefore, this study suggests mortality projection based on the projection of the skewness for the mortality that has been applied to appropriately reflect the improvement trend of the mortality rate. This paper calculates monthly payments using future mortality rates based on the projection of the skewness of the mortality. As a result, the mortality rates based on this method less reflect the mortality improvement effect than the mortality rates based on a traditional LC model and a larger pension amount is calculated. In conclusion, this method is useful to forecast future mortality trend results in a significant reduction of longevity risk. It can also be used as a risk management method to pay appropriate monthly payments and prevent insufficient payment due to overpayment by the issuing institution and the guarantee institution of the reverse mortgage.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.347-373
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• 2021

Over the past 50 years, explorative research on the nation's mortality decline patterns has showed a decrease in age-specific mortality rates in all age groups, but there were different improvement patterns in specific mortality rates depending on ages and periods. Greater distinct improvement was observed in mortality rates among women than men, and there was a noticeable improvement in mortality rates in certain groups especially in the more recent decades, revealing a structural change in the overall trends regarding death periods. In this paper, we compare various stochastic mortality models considering cohort effects for mortality projection using Korean female mortality data and further explore the uncertainty related to projection. It also created age-specific mortality rates and life expectancy for women until 2067 based on the results of the analysis, and compared them with future age-specific mortality rates and life expectancy provided by the national statistical office (KOISIS). The best optimal model could vary depending on data usage periods. however, considering the overall fit and predictability, the PLAT model would be regarded to have appropriate predictability in terms of the mortality rates of women in South Korea.

• East Asian mathematical journal
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• v.35 no.3
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• pp.305-318
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• 2019

Over the past decades, the Lee-Carter model [1] has attracted much attention from various demography-related fields in order to project the future mortality rates. In the Lee-Carter model, the speed of mortality improvement is stochastically modeled by the so-called mortality index and is used to forecast the future mortality rates based on the time series analysis. However, the modeling is applied to long time series and thus an important structural change might exist, leading to potentially large long-term forecasting errors. Therefore, in this paper, we are interested in detecting the structural change of the Lee-Carter model and investigating the actuarial implications. For the purpose, we employ the tests proposed by Coelho and Nunes [2] and analyze the mortality data for six countries including Korea since 1970. Also, we calculate life expectancies and whole life insurance premiums by taking into account the structural change found in the Korean male mortality rates. Our empirical result shows that more caution needs to be paid to the Lee-Carter modeling and its actuarial applications.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.557-573
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• 2019

Mortality study is an essential component of actuarial risk management for life insurance policies, annuities, and pension plans. Life expectancy has drastically increased over the last several decades; consequently, longevity risk associated with annuity products and pension systems has emerged as a crucial issue. Among the various aspects of mortality study, a consideration of the cause-of-death mortality can provide a more comprehensive understanding of the nature of mortality/longevity risk. In this case study, the cause-of-mortality data in Korea and the US were analyzed along with a multinomial logistic regression model that was constructed to quantify the impact of mortality reduction in a specific cause on actuarial values. The results of analyses imply that mortality improvement due to a specific cause should be carefully monitored and reflected in mortality/longevity risk management. It was also confirmed that multinomial logistic regression model is a useful tool for analyzing cause-of-death mortality for actuarial applications.

• Journal of Preventive Medicine and Public Health
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• v.46 no.2
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• pp.74-81
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• 2013

Objectives: The objective of this study was to evaluate the performance of risk-adjusted mortality models for colorectal cancer surgery. Methods: We investigated patients (n=652) who had undergone colorectal cancer surgery (colectomy, colectomy of the rectum and sigmoid colon, total colectomy, total proctectomy) at five teaching hospitals during 2008. Mortality was defined as 30-day or in-hospital surgical mortality. Risk-adjusted mortality models were constructed using claims data (basic model) with the addition of TNM staging (TNM model), physiological data (physiological model), surgical data (surgical model), or all clinical data (composite model). Multiple logistic regression analysis was performed to develop the risk-adjustment models. To compare the performance of the models, both c-statistics using Hanley-McNeil pair-wise testing and the ratio of the observed to the expected mortality within quartiles of mortality risk were evaluated to assess the abilities of discrimination and calibration. Results: The physiological model (c=0.92), surgical model (c=0.92), and composite model (c=0.93) displayed a similar improvement in discrimination, whereas the TNM model (c=0.87) displayed little improvement over the basic model (c=0.86). The discriminatory power of the models did not differ by the Hanley-McNeil test (p>0.05). Within each quartile of mortality, the composite and surgical models displayed an expected mortality ratio close to 1. Conclusions: The addition of clinical data to claims data efficiently enhances the performance of the risk-adjusted postoperative mortality models in colorectal cancer surgery. We recommended that the performance of models should be evaluated through both discrimination and calibration.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.393-406
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• 2015

We examine how to model mortality risk using the adaptation of the mean-reverting processes for the two factor model proposed by Cairns et al. (2006b). Mortality improvements have been recently observed in some countries such as United Kingdom; therefore, we assume long-run mortality converges towards a trend at some unknown time and the mean-reverting processes could therefore be an appropriate stochastic model. We estimate the parameters of the two-factor model incorporated with mean-reverting processes by a Metropolis-Hastings algorithm to fit United Kingdom mortality data from 1991 to 2015. We forecast the evolution of the mortality from 2014 to 2040 based on the estimation results in order to evaluate the issue price of a longevity bond of 25 years maturity. As an application, we propose a method to quantify the speed of mortality improvement by the average mean reverting times of the processes.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5189-5193
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• 2012

Kemerovo is an industrial region of the Russian Federation characterized by highly developed mining, chemical, metallurgical and power industries. Many of the factories were closed down due to the socioeconomical crisis in the early 90's, and economic potential of the survivors has also decreased significantly. Paradoxically, this has led to the improvement of the ecological situation in the region and elimination of exposure to many chemical carcinogens. This factor, in combination with the improvement of oncological care, might be expected to have lead to a decline of cancer incidence and mortality in the region. To assess trends of cancer incidence and mortality in Kemerovo Region, we therefore carried out an analysis of relevant epidemiological data during 1991-2010. In fact, a significant increase of cancer incidence overall was revealed during 2001-2010. Male cancer incidence was significantly higher than female cancer incidence. Regarding gastric cancer incidence, statistically significant differences during 2001-2010 were found only for men, and male incidence exceeded female incidence. Concerning colorectal cancer incidence, it was lower during 2001-2005 and 2006-2010 as compared to the period of 1991-1996. Lung cancer incidence was significantly higher during 1991-2000 compared to 2001-2010. Among urban populations, cancer incidence was higher in comparison with rural population, but a gradual steady convergence of trends of cancer incidence among urban and rural populations was noted. Lung cancer, breast cancer, colorectal cancer, non-melanoma skin cancer, and gastric cancer are the most prevalent cancer forms in Kemerovo Region. There were no differences in cancer mortality between 2001-2005 and 2006-2010; however, male cancer mortality exceeded female cancer mortality. A similar situation was observed for gastric cancer, colorectal cancer, and lung cancer. Cancer mortality among urban populations exceeded mortality among rural population, for both genders. We suggest that these data can be used for development of modern programs of cancer prevention and early diagnostics in industrial regions of Siberia.

• Annals of Rehabilitation Medicine
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• v.42 no.6
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• pp.838-845
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• 2018

Objective To investigate the effect of a rehabilitation program in terms of De Morton Mobility Index (DEMMI) score, in hematologic cancer patients after chemotherapy. Methods Hematologic cancer patients admitted for chemotherapy were reviewed. They received a rehabilitation program during their hospital stay. DEMMI score measurement was performed, before and after rehabilitation. Demographics, diagnosis, chemotherapy information, rehabilitation program duration, mortality, body mass index (BMI), and laboratory test results were collected. For analysis, patients were classified according to diagnosis (multiple myeloma, leukemia, and others), mortality, and additional chemotherapy. Results There was statistically significant improvement in DEMMI score of 10.1 points (95% confidence interval, 5.9-14.3) after rehabilitation. It was more evident in the multiple myeloma group, and they revealed less mortality. When patients were divided according to mortality, survivors received the program earlier, and in a shorter period than in mortality cases. Although survivors revealed higher initial DEMMI score, improvement after rehabilitation did not differ significantly. Conclusion In hematologic cancer patients, rehabilitation program was effective for recovery from deconditioning, revealing significant increase in DEMMI score. Multiple myeloma patients may be good candidates for rehabilitation. Rehabilitation could be sustained during chemotherapy and for high-risk patients.

• Quality Improvement in Health Care
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• v.7 no.2
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• pp.218-228
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• 2000

Background : Among 'structure', 'process' and 'outcome' approaches, outcome evaluation is considered as the most direct and best approach to assess the quality of health care providers. Risk-adjustment is an essential method to compare outcome across providers. This study has aims to judge performance of hospitals by severity adjusted mortality rates of coronary artery bypass graft (CABG) surgery. Methods : Medical records of 584 patients who got the CABG surgery in 6 general hospitals during 1996 and 1997 were reviewed by trained nurses. The MedisGroups was used to quantify severity of patients. The predictive probability of death was calculated for each patient in the sample from a multivariate logistic regression model including the severity score, age and sex. For evaluation of hospital performance, we calculated ratio of observed number to expected number of deaths and z score [(observed number of deaths - expected number of deaths)/square root of the variance in the number of deaths], and compared observed mortality rate with confidence interval of adjusted mortality rate for each hospital. Results : The overall in-hospital mortality was 7.0%, ranged from 2.7% to 15.7% by hospital. After severity adjustment the mortality by hospital was from 2.7% to 10.7%. One hospital with poor performance was distinctly divided from others with good performance. Conclusion : In conclusion, severity-adjusted mortality rate of CABG surgery might be applied as an indicator for hospital performance evaluation in Korea. But more pilot studies and improvement of methodologies has to be done to use it as quality indicator.

• Korea journal of population studies
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• v.9 no.2
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• pp.53-66
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• 1986

This study was carried out to determine the mortality level and it's related demographic factors in Korea since 1942. In order to clarify the changes in structure of mortality and the causes of death, the indices such as Crude Death Rate(CDR) or Life Expectancy at Birth were used. The author examined the mortality levels and major causes of death and performed the relevant demographic analysis. The followings are the summary of this study: 1. The CDR declined rapidly till 1960's. Such improvement slowed down from 1960's to mid 1970's and stabilized afterwards. It was due to the change of age composition, namely, the increase of aging population. 2. The Life Expectancy at Birth increased rapidly till mid 1960's. But elongation of the Life Expectancy slowed down after then. Especially in female, it slowed down more. 3. Changing patterns of major causes of death summarize that, till 1960's infectious diseases were major causes of death, but recently non-infectious diseases like chronic degenerative diseases became more prevalent. 4. The elongation of Life Expectancy at Birth till mid 1960's was mainly resulted by $_4{q}_1$. But the major contributing factor of the improvement in Life Expectancy at Birth in female is he reduction of $_$\infty${q}_{50}$ recently. In male, the improvement in Life Expectancy at Birth is due to the reduction of $_1{q}_0$. recently. 5. The age-sex-specific mortality rates revealed that $_n{q}_x$ declined in common throughout the period, even though there exists some variability of their ranges as age changes. Consequently, this study seems to suggest that the demographic transition in Korea occurred between late 1960's and early 1970's. In other words, the rapid change before late 1960's was eased in early 1970's. The slow change in this period caused a stabilizing pattern. Therefore, the population change is expected to be stabilized continuously.