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논문 기본 정보

자료유형
학술저널
저자정보
Jung Yoon-Sun (Department of Public Health Graduate School Korea University Seoul Korea) Kim Young-Eun (Department of Big Data Strategy National Health Insurance Service Wonju Korea.) Park Hyesook (Department of Preventive Medicine College of Medicine Ewha Womans University Seoul Korea.) Oh In-Hwan (Department of Preventive Medicine Kyung Hee University School of Medicine Seoul Korea.) 조민우 (울산대학교) 옥민수 (울산대학교) Go Dun-Sol (Department of Health Care Policy Research Korea Institute for Health and Social Affairs Sejong Kore) Yoon Seok-Jun (Department of Preventive Medicine Korea University College of Medicine of Seoul Korea.)
저널정보
대한예방의학회 예방의학회지 예방의학회지 제54권 제5호
발행연도
2021.9
수록면
293 - 300 (8page)
DOI
10.3961/jpmph.21.478

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The study aims to examine the current status and differences in the burden of disease in Korea during 2008-2018. We calculated the burden of disease for Koreans from 2008 to 2018 using an incidence-based approach. Disability adjusted life years (DALYs) were expressed in units per 100 000 population by adding years of life lost (YLLs) and years lived with disability (YLDs). DALY calculation results were presented by gender, age group, disease, region, and income level. To explore differences in DALYs by region and income level, we used administrative district and insurance premium information from the National Health Insurance Service claims data. The burden of disease among Koreans showed an increasing trend from 2008 to 2018. By 2017, the burden of disease among men was higher than that among women. Diabetes mellitus, low back pain, and chronic lower respiratory disease were ranked high in the burden of disease; the sum of DALY rates for these diseases accounted for 18.4% of the total burden of disease among Koreans in 2018. The top leading causes associated with a high burden of disease differed slightly according to gender, age group, and income level. In this study, we measured the health status of Koreans and differences in the population health level according to gender, age group, region, and income level. This data can be used as an indicator of health equity, and the results derived from this study can be used to guide community-centered (or customized) health promotion policies and projects, and for setting national health policy goals.

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