• 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.

• 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.

• 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.

• 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.

• Journal of Preventive Medicine and Public Health
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• v.35 no.4
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• pp.331-339
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• 2002

Objectives : To measure DALE (Disability-Adjusted Life Expectancy) in Korea to find out how long Koreans live in a state of full heath. Methods : DALE was calculated using the life table of 1999 and the disability prevalence from the National Health Interview Survey (NHIS), which was conducted with a sample of 13,523 households in 1998. The disability prevalence was measured using the annual prevalence of the long-term limitation of activities, which were divided into classes 1, 2, 3, 4, 5 and 6 according to the severity of the limitation. The disability weights were measured for each 6 class by conducting a survey of 16 healthcare professionals. The severity-adjusted disability prevalence was calculated by multiplying the disability prevalence of each class by the disability weights respectively. Healthy life years lost due to disability was calculated by multiplying the life expectancy by the severity-adjusted disability prevalence. Finally DALE was measured as the life expectancy minus healthy life years lost due to disability. Results : DALE for 1999, which refers to the expectation of equivalent years of good health, were 72.5, 69.5 and 75.3 years, for total, for males and for females, respectively. The percentages for DALE out of the life expectancy were 95.8, 96.6 and 94.4% for total, for males and for females, respectively. Conclusions : DALE is a newly developed indicator, which could effectively show the healthy life expectancy of populations. A greater notice and use of DALE would be expected as life expectancies increase and the quality of life changes in Korea.

• 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.

• Journal of Technologic Dentistry
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• v.35 no.4
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• pp.405-414
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• 2013

Purpose: The purpose of this study was to examine the relationship of the general characteristics of health-related majors to their life expectancy scale, depression scale, health perception scale, subjective wellbeing scale, somatic symptom scale and college life stress scale. And it's also meant to analyze influential factors for their stress about college life. Methods: The subjects in this study were the students who were in the department of dental laboratory technology and the department of dental hygiene at a college located in the region of Iksan, North Jeolla Province. Data were gathered in November and December, 2012. The life expectancy scale, depression scale, health perception scale, subjective wellbeing scale, physical symptom scale, somatic symptom scale and college life stress scale of the general characteristics were analyzed by t-test and one way analyses of variance (ANOVA) and the Duncan's multiple range test at the 95% confidence level to assess the statistical significance. And stepwise multiple regression analysis was conducted to determine what factors would affect the stress of the students about college life. The data were analyzed with the windows ver. 12.0(SPSS GmbH, Germany) statistical software program. Results: Among the general characteristics, there were significant differences according to gender and age in all the variables that were life expectancy scale, depression scale, health perception scale, subjective wellbeing scale, physical symptom scale and college life stress scale. 61.3% of the students responded they slept for six hours or less, and the respondents who slept for six hours or less scored significantly statistically lower in health perception scale, subjective wellbeing scale and physical symptom scale. As for college life stress, the respondents who got depressed more often, whose subjective peace or happiness was lower, whose life expectancy was lower, who had worse physical symptoms, whose living standard was lower and whose academic year was lower were under heavier stress about their college lives. Conclusion: As the worse physical health and worse mental health(life expectancy, depression, health perception, subjective wellbeing and physical symptoms, etc.) of the college students led to heavier stress about college life, how to promote their physical health and mental health should discreetly be considered, and every necessary measure should be taken to improve their physical and mental health.