• Journal of Preventive Medicine and Public Health
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• v.53 no.2
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• pp.143-148
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• 2020

Objectives: We calculated life expectancy and inequalities therein by income for the period of 2016-2018 across the 253 electoral constituencies of the 20th National Assembly election in Korea. Methods: We obtained population and death data between 2016 and 2018 from the National Health Information Database and constructed abridged life tables using standard life table procedures according to gender and income quintiles for the electoral constituencies of the 20th National Assembly election held in 2016. Results: Life expectancy across the 253 constituencies ranged from 80.51 years to 87.05 years, corresponding to a gap of 6.54 years. The life expectancy difference by income across the 253 constituencies ranged from 2.94 years to 10.67 years. In each province, the difference in life expectancy by income across electoral constituencies was generally greater than the inter-constituency differences. Constituencies in capital and metropolitan areas showed a higher life expectancy and a lower life expectancy difference by income than constituencies in rural areas. Conclusions: Pro-rich inequalities in life expectancy by income existed in every electoral constituency in Korea. Both intra-constituency and inter-constituency socioeconomic inequalities in health should be highlighted in future policy-making in the National Assembly.

• The Korean Journal of Health Service Management
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• v.5 no.3
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• pp.123-132
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• 2011

To evaluate the impact of avoidable mortality on the changes in life expectancy at birth in Korea. Standard life table techniques and the Arriaga method were used to calculate and to decompose life expectancy changes by age, effects and groups of causes of avoidable mortality among two periods(1990-2000 and 2000-2009). A list of causes of avoidable mortality reached by consensus and previously published in Spain was used. Mortality in young adults produced a reduction in life expectancy at birth during the 1990-2000, but there was an important increase in life expectancy at birth during the 2000-2009; in both cases, this was the result of factors amenable to health policy interventions. The highest improvement in life expectancy at birth was due to non-avoidable causes, but avoidable mortality through health service interventions showed improvements in life expectancy at birth in those elderly people than 1 year and in those younger. Making a distinction between several groups of causes of avoidable mortality and using decomposition by causes, ages and effects allowed us to better explain the impact of avoidable mortality on the life expectancy at birth of the whole population and gave a new dimension to this indicator that could be very useful in public health.

• Journal of Preventive Medicine and Public Health
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• v.55 no.1
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• pp.1-9
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• 2022

An index that evaluates the health level of a population group considering both death and loss of function due to disease is called a summary measure of population health (SMPH). SMPHs are broadly divided into life year indices and life expectancy indices, the latter of which comprise healthy life expectancy (HLE). HLE is included as a policy target in various national and regional level healthcare plans, and the term "HLE" is commonly used in academia and by the public. However, the overall level of understanding of HLE-such as the precise definition of HLE and methods of calculating HLE-still seems to be low. As discussed in this study, the types of HLE are classified into disability-free life expectancy, disease-free life expectancy, quality-adjusted life expectancy, self-rated HLE, and disability-adjusted life expectancy. Their characteristics are examined to facilitate a correct understanding and appropriate utilization of HLE. In addition, the Sullivan method, as a representative method for calculating HLE, is presented in detail, and major issues in the process of calculating HLE, such as selection of the population group and age group, estimation of death probability, calculation of life years, and incorporation of health weights, are reviewed. This study will help researchers to select an appropriate HLE type and evaluate the validity of HLE research results, and it is expected to contribute to the vitalization of HLE research.

• Health Policy and Management
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• v.18 no.1
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• pp.108-126
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• 2008

Summary measures of population health or SMPH is an index which can describe morbidity as well as mortality. Summary measures of population health can be divided into health-adjusted life years which is a life expectancy measure and disability-adjusted life years which represents the gap between the ideal health status and the current health status. This study aims at estimating health-adjusted life expectancy(HALE) which is a measure of health-adjusted life years, by calculating life expectancy adjusted by health status using EQ-5D. The mortality data was obtained from the life table of 2005 which was published by the National Statistical Office and the health status by sex and age was obtained from the EQ-5D scores using the third National Health and Nutrition and Examination Survey in 2005. With these mortality and morbidity data, health-adjusted life expectancy was calculated using Sullivan's method. The study results showed that the health-adjusted life expectancy of males and females was 67.49 and 69.61, respectively, while the life expectancy of males and females was 75.14 and 81.89. In other words, Korean males and females lose 7.65 and 12.28, respectively, from the decrease of quality of life due to diseases and/or injuries. These results can further be interpreted that males lose 10.2% of their life expectancy and females 15.0%. This study suggests that it may be possible to monitor population's health-adjusted life expectancy by continuing to include health-related quality of life measures such as EQ-5D in national health surveys like the National Health and Nutrition and Examination Survey.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.61-68
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• 2022

In this paper, the change history of various types of MV (Medium Voltage) cables was investigated. In addition, the statistical life expectancy of each type was calculated by using the operation data and the failure data. For cut-off year, 10 years was applied, and realistically applicable statistical life expectancy was calculated by correcting the cause of failure entered by mistake. The life expectancy of FR-CNCO-W was calculated as 51.2 years, CNCV-W 38.1 years, and CNCV 31.4 years and the overall average is 33.8 years. Currently, the life expectancy of TR CNCV-W is 29.4 years, but it is estimated that the lifespan will be extended if failure data is accumulated. As a result, it is expected that life expectancy results can be applied to Asset Management System (AMS) in the future.

• Korea journal of population studies
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• v.19 no.1
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• pp.123-137
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• 1996

The goal of this study was to measure the level of health quantitatively by combining mortality and morbidity level of the Korean people. The 1989 Life Table was used for the mortality data. For the morbidity data, the 15-day morbidity survey (10, 940) the hospitalized patient survey (1, 770), chronic morbidity survey (7, 241) of the 1989 National Health Sunvey conducted by Korean Institute of Health and Social Affairs were utilized. The life table analysis technique of Sullivan was adopted. The morbidity period and disability period required for this method were estimated by measuring disability period rate and disability rate. The disability free life expectancy was estimated by excluding disability life expectancy from life expectancy. In case of males, the disability-free life expectancy at birth was 60.48 years. In case of females, the disability-free life expectancy at birth was 63.80 years. The percent of disability-free life expectancy to life expectancy was 90.63% at birth in case of males and 85.20% in case of females. The portion of females was lower than that of males in all age brackets. Therefore, the percent of time spent without disability condition to life expectancy was higher for females than males. Estimating disability-free life expectancy by region, it was 61.52 years at birth in urban area and 59.34 years in rural area in case of males. In case of females, it was estimated to be 64.60 years in urban area and 63.08 years in rural area. The life expectancy of Koreans was 66.73 years for males and 74.88 years for females, 8.15 years higher than males while disability-free life expectancy was 60.48 years for males, 63.80 years for females, only 3.32 years higher than males.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.801-808
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• 2021

The issue of the relationship between environmental degradation and human health has been widely addressed by medical doctors. However, economists have sparsely debated it. The release of carbon dioxide (CO2) into the air can cause several environmental problems and, thus, it can affect human health. Therefore, it is imperative to examine the effect of CO2 emissions on life expectancy in the D-8 countries (Malaysia, Indonesia, Bangladesh, Nigeria, Egypt, Iran, Pakistan, and Turkey) from 1992 to 2017. The panel ARDL method is employed and, then, the PMG estimator is selected. The results show that economic growth, population growth and health expenditure can significantly and positively affect life expectancy, but CO2 emissions can have a significant and negative effect on life expectancy. Since, the major findings reveal that life expectancy can be explained by CO2 emissions. Hence, it is important to formulate policies on reducing CO2 emissions so that life expectancy will not be affected. Energy diversification policies should be formulated or improved in some countries. This is to ensure that the countries are not highly dependent on non-renewable energy that can harm the environment. The government should increase its expenditure on the health sector to save more lives by extend human lifespan.

• Korea journal of population studies
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• v.16 no.2
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• pp.65-83
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• 1993

The purpose of this study is estimate limits of Korean life expectancy at birth by 'Gompertz growth curse Model', 'Cause-Elimination Model' and Multidimensional models of Senescencee and Mortality'. Data used in Gompertz curve were obtained from all life tables published from 1905 to 1990 in Korea, and life expectancies at birth of eighteen groups were selected at five-year interval in consideration of time-series changes. Data used in Cause-Elimination Model are 'Cause of Death statistics in 1991' published in 1992 by National Bureau of Statistics of Korea and 'life table of 1989' published in 1990 by National Bureau of Statistics, Economic Planning Board of Korea. The materials are all classifiable death data, 119, 253 cases of male and 82, 420 cases of female, which is from 1991 Causes of Death statistics. The cases of death analyzed belong to one of 8 categories; i.e., Infectious and Parasitic Diseases(001-139; with notation of Infectious Diseases), Malignant Neoplasms(140-208), Hypertensive Diseases(401-405), Ischemic Heart Dieases and Diseases of Pulmonary Circulation and Other Forms of Heart Diseases(410-429;with notation of Heart Disease), Cerebrovascular Diseases(430-438), Chronic Liver Diseases and Cirrhosis(571; with notation of Liver Diseases), Injury and Poisoning(800-999) and all other disease. Data used in 'Multidimensional models of senescence and mortality' were life table of 1989 published by National Bureau of statistics, Economic Planning Board of Korea and life table of 1970, 1978-79, 1983, 1985 and 1987. The major findings may be summarised as follows: 1. Estimate equations of Gompertz growth curve using life expectancy at birth during the 1905-1990 period are as the following. Male : y = 88.047697 $\times$ $0.199690^{0.903381x}$ Female : y = 95.632828 $\times$ $0.199690^{0.903381x}$ Limits of life expectancy at birth, which were estimated by Gompertz growth curve, are 88.05 for male and 95.63 for female. 2. The effect on life expectancy at birth eliminationg all causes death is 14.04 years(for male) and 10.86 years(for female). Astonishingly, eliminating the malignant neoplasms increase life expectancy at birth by 2.85 years for male 2.03 years for female in 1991. In table 8 we show the effect on life expectancy at birth of separately eliminating each of the 8 categorical causes of death. The theoretical limit to life expectancy by Cause-Elimination Model is 80.96 for male and 85.82 for female. 3. If the same rate of delay [0.376 year(male), 0.435 year(femable) per calendar year] continued, then life expectancy at birth would reach 74.82(male) years and 84, 10(female) years in 2010. With 14.04-years(male) and 10.86-years(female) effect attributable in 2010 would be 88.86 years(male) and 94.96(femable) years. 4. 'Multidimensional models of senescence and death' permits calculations of the value of the attribution coefficient (B), percent of loss per year of physiologic function. The results of Ro and B during the 1970-1989 period are listed in table 9. Estimate of limit to Korean life expectancy at birth by 'Multidimensional models of senescence and death' is 99.47 years for male and 104.74 years for female in 1989.

• The Journal of Korean Society for School & Community Health Education
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• v.22 no.2
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• pp.75-91
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• 2021

Purpose: The purpose of this article is to clearly describe research trends on health life expectancy using oral health indicators that have been published from 2010 to 2020 then suggest the direction of future research. Methods: Online academic databases in English (PubMed, Web of Science and Embase) were used to find those articles by applying a variety of keywords, including terms (adjusted life year, adjusted life expectancy, dental and oral). We identified relevant articles based on the following classification method of Mathers: (1) health gaps, (2) health expectancies. Results: Among 1,728 articles from the online databases, the final 13 studies satisfied the inclusion criteria and were selected for analysis. Health life expectancy studies indicate that research growth was recently achieved overseas. Among the literature collected in this study, 10 studies using health gap indicators yielded seven Disability-Adjusted Life Year (DALY), and three calculated Quality-Adjusted Life Year (QALY), which differed in the nature of the survey data used in the study measuring DALY and QALY. There are only three health expectancies and the number of papers were smaller than the health gap study. Conclusion: Establishing a foundation to calculate health life expectancy indicators through the development and improvement of oral health level are needed. More studies in the area of health life expectancy estimation research is based on actual prevalence and oral health-related quality of life are also needed.

• International Journal of Contents
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• v.8 no.3
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• pp.52-56
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• 2012

This study examines whether the infant mortality rate and life expectancy at birth are affected by health care expenditure in Korea. It can be provisionally concluded that the infant mortality rate tends to be affected by the health system itself in the long-run, whereas life expectancy at birth is immediately affected by health-related facilities such as the number of physicians and number of hospital beds in the short-run. Therefore, the health-related system should be well established to improve the infant mortality rate. On the contrary, physical capital such as life-prolonging medical technologies has to be accumulated to improve life expectancy at birth.