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.
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Korean summary
건강수명의 유형은 무장애기대수명, 질병 없는 기대수명, 질보정기대수명, 자가평가보정 기대수명, 장애보정기대수명으로 분류된다. 건강수명의 올바른 이해와 적절한 활용을 돕기 위해 이들의 특성을 검토하였다. 이번 연구는 연구자들이 적절한 건강수명 유형을 선택하고 건강수명 연구 결과의 타당성을 평가하는 데 도움이 될 것이며, 건강수명 연구의 활성화에 기여할 것으로 기대된다.
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The National Health Plan 2030 (HP2030) started to be prepared in 2017 and was completed and announced in December 2020. This study presents an overview of how it was established, the major changes in policies, its purpose, and future directions. This study analyzed the steps taken in the past 4 years to establish HP2030 and reviewed major issues at the international and governmental levels based on an evaluation of HP2020 and its content. HP2030 establishes 6 divisions and 28 topic areas, and it will continue to expand investments in health with a total budget of 2.5 trillion Korean won. It also established goals to enhance health equity for the first time, with the goal of calculating healthy life expectancy in a way that reflects the circumstances of Korea and reducing the gap in income and healthy life expectancy between regions. The establishment of HP2030 is significant in that it constitutes a sustainable long-term plan with sufficient preparation, contains policy measures that everyone participates in and makes together, and works towards improvements in universal health standards and health equity. With the announcement of HP2030, which includes goals and directions of the national health policy for the next 10 years, it will be necessary to further strengthen collaboration with relevant ministries, local governments, and agencies in various fields to concretize support for prevention-centered health management as a national task and to develop a health-friendly environment that considers health in all policy areas.
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Korean summary
본 연구는 지난 17년부터 4년간 준비한 국민건강증진종합계획2030이 발표됨에 따라 수립경과와 주요 변화정책을 분석하고, 수립의 의의를 검토하여 향후 추진방향을 제시하고자 한다. 국민건강증진종합계획2030의 수립은 충분한 준비기간을 통한 지속가능한 중장기 계획의 수립, 모든 사람에 함께 참여하고 만들어가는 정책으로서의 전환, 보편적인 건강수준 향상과 건강형평성 제고를 했다는데 그 의의가 있다 향후 10년간의 국가 건강정책의 목표와 방향을 담은 HP2030 발표를 계기로, 모든 정책 영역에서 건강을 고려하는 건강친화적 환경 구축을 위해 관련 부처와 지자체, 다양한 분야의 주체들과 협력을 강화해야 하겠다.
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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.
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Korean summary
이 연구는 2016년 치뤄진 제20대 국회의원 선거구 253개에서 2016-2018년의 기대수명을 산출하고, 소득 상위 20%와 소득 하위 20% 간 기대수명 격차를 제시하였다. 연구 결과, 253개 모든 선거구에서 소득 상위 20%가 소득 하위 20%보다 기대수명이 높게 나타났으며, 선거구 내의 소득에 따른 기대수명 격차가 선거구들 간의 기대수명 차이보다 더 큰 경향을 보였다. 기대수명의 선거구 간 격차를 줄이고, 선거구 내의 소득 계층 간 기대수명 격차를 해소하기 위한 입법적 조치를 마련하는 데에 이 연구의 결과가 근거자료로 유용하게 사용되기를 기대한다.
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Objectives Subjective life expectancy (SLE) has been found to show a significant association with mortality. In this study, we aimed to investigate the major factors affecting SLE. We also examined whether any differences existed between SLE and actuarial life expectancy (LE) in Korea. Methods: A cross-sectional survey of 1000 individuals in Korea aged 20-59 was conducted. Participants were asked about SLE via a self-reported questionnaire. LE from the National Health Insurance database in Korea was used to evaluate differences between SLE and actuarial LE. Age-adjusted least-squares means, correlations, and regression analyses were used to test the relationship of SLE with four categories of predictors: demographic factors, socioeconomic factors, health behaviors, and psychosocial factors. Results: Among the 1000 participants, women (mean SLE, 83.43 years; 95% confidence interval, 82.41 to 84.46 years; 48% of the total sample) had an expected LE 1.59 years longer than that of men. The socioeconomic factors of household income and housing arrangements were related to SLE. Among the health behaviors, smoking status, alcohol status, and physical activity were associated with SLE. Among the psychosocial factors, stress, self-rated health, and social connectedness were related to SLE. SLE had a positive correlation with actuarial estimates (r=0.61, p<0.001). Gender, household income, history of smoking, and distress were related to the presence of a gap between SLE and actuarial LE. Conclusions: Demographic factors, socioeconomic factors, health behaviors, and psychosocial factors showed significant associations with SLE, in the expected directions. Further studies are needed to determine the reasons for these results.
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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. RESUJLTS: 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.
OBJECTIVES This study introduced the healthy life-year(HeaLY), a composite indicator of disease burden, and used it to estimate the burden of major cancers in Korea. METHODS: We collected data from the national death certificate database, the national health insurance claims database and the abridged life table. This data was used to create a spreadsheet and estimate the burden of major cancers by sex in terms of HeaLYs. RESULTS: The burden of 10 major cancers for males was 2,248.97 person-year in terms of HeaLYs. Stomach cancer, liver cancer, and lung cancer were responsible for 75.2% of the burden of 10 major cancers The disease burden of 10 major cancers for females was estimated to be 1,567.58 person-years. About two thirds of HeaLYs lost were from stomach cancer, liver cancer, lung cancer, colorectal cancer, and breast cancer. The rankings among 10 major cancers were somewhat different in terms of both HeaLYs and deaths as the HeaLY method considers both mortality and morbidity. CONCLUSIONS: Despite the limitations of the data sources, we conclude that HeaLY can aid in setting policy priorities concerning major cancers by estimating the disease burden of these cancers. Time-series analysis of the disease burden using HeaLY and DALY will elucidate the strengths and weaknesses of both methods.
OBJECTIVES The aim of this study was to estimate the burden of disease through an analysis of Years of Life Lost due to premature deaths, one component of the Disability-Adjusted Life Years (DALY). In addition, the cause of death statistics were adjusted to improve validity, and the results were compared with those of the Global Burden of Disease (GBD). METHODS: In closely following the approach taken in the original GBD study, most of the explicit assumptions and the value judgments were not changed. However, the statistics for some problematic concerns such as deaths of infants or those due to senility, were adjusted. Deaths, standard expected years of life lost (SEYLL), and potential years of life lost (PYLL) were computed using vital registration data compiled by the National Statistical Office. RESULTS: The burden for males is 1.8 and 2.3 times higher than that for females, according to SEYLL and PYLL, respectively. The proportions of deaths due to Group I, II, and III causes are 5.4%, 80.4%, and 14.3%, respectively, for PYLL, but in a major shift from Group II to III they are 6.3%, 66.2%, and 27.5%, respectively, for SEYLL. The proportion of Group III causes in Korea, 27.5%, is extremely high when compared to 10.1% for the world, 7.6% for developed countries, and 10.7% for developing countries. CONCLUSIONS: Estimation results showed that the total burden due to premature deaths is smaller than that for the entire world but larger than that for developed countries. The disease structure of Korea has changed to resemble that of developed countries. Also, an overly large portion of the total burden in Korea stems from injuries arising from car accidents.
Sixty-two medical records of patients with coal workers' pneumoconiosis who died in hospital as coal workers' pneumoconiosis were analyzed for study of the relationship between forced expiratory volume in one second(FEV1) and life expectancy in coal workers' pneumoconiosis. In the group who died of asphyxia from hemoptysis, life expectancy were well fitted with FEV1 (p<0.05). But others were not well fitted to simple linear regression equation. The prevalence of ECG sign of cor pulmonale was more in the group of cardiorespiratory failure than asphyxia group. So, in the case of far advanced cor pulmonale, it was difficult to predict life expectancy by simple linear regression equation.