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      Incidence and case fatality of stroke in Korea, 2011-2020

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          Abstract

          OBJECTIVES

          Stroke remains the second leading cause of death in Korea. This study was designed to estimate the crude, age-adjusted and age-specific incidence rates, as well as the case fatality rate of stroke, in Korea from 2011 to 2020.

          METHODS

          We utilized data from the National Health Insurance Services from January 1, 2002 to December 31, 2020, to calculate incidence rates and 30-day and 1-year case fatality rates of stroke. Additionally, we determined sex and age-specific incidence rates and computed age-standardized incidence rates by direct standardization to the 2005 population.

          RESULTS

          The crude incidence rate of stroke hovered around 200 (per 100,000 person-years) from 2011 to 2015, then surged to 218.4 in 2019, before marginally declining to 208.0 in 2020. Conversely, the age-standardized incidence rate consistently decreased by 25% between 2011 and 2020. When stratified by sex, the crude incidence rate increased between 2011 and 2019 for both sexes, followed by a decrease in 2020. Age-standardized incidence rates displayed a downward trend throughout the study period for both sexes. Across all age groups, the 30-day and 1-year case fatality rates of stroke consistently decreased from 2011 to 2019, only to increase in 2020.

          CONCLUSIONS:

          Despite a decrease in the age-standardized incidence rate, the total number of stroke events in Korea continues to rise due to the rapidly aging population. Moreover, 2020 witnessed a decrease in incidence but an increase in case fatality rates.

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          Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

          Summary Background How long one lives, how many years of life are spent in good and poor health, and how the population’s state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life-years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Socio-demographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years (95% uncertainty interval 7·1–7·8), from 65·6 years (65·3–65·8) in 1990 to 73·0 years (72·7–73·3) in 2017. The increase in years of life varied from 5·1 years (5·0–5·3) in high SDI countries to 12·0 years (11·3–12·8) in low SDI countries. Of the additional years of life expected at birth, 26·3% (20·1–33·1) were expected to be spent in poor health in high SDI countries compared with 11·7% (8·8–15·1) in low-middle SDI countries. HALE at birth increased by 6·3 years (5·9–6·7), from 57·0 years (54·6–59·1) in 1990 to 63·3 years (60·5–65·7) in 2017. The increase varied from 3·8 years (3·4–4·1) in high SDI countries to 10·5 years (9·8–11·2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1·0 year (0·4–1·7) in Saint Vincent and the Grenadines (62·4 years [59·9–64·7] in 1990 to 63·5 years [60·9–65·8] in 2017) to 23·7 years (21·9–25·6) in Eritrea (30·7 years [28·9–32·2] in 1990 to 54·4 years [51·5–57·1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1·4 years (0·6–2·3) in Algeria to 11·9 years (10·9–12·9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75·8 years [72·4–78·7]) and males (72·6 years [69·8–75·0]) and the lowest estimates were in Central African Republic (47·0 years [43·7–50·2] for females and 42·8 years [40·1–45·6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41·3% (38·8–43·5) for communicable diseases and by 49·8% (47·9–51·6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40·1% (36·8–43·0), although age-standardised DALY rates decreased by 18·1% (16·0–20·2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low SDI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health. Funding Bill & Melinda Gates Foundation.
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            An updated definition of stroke for the 21st century: a statement for healthcare professionals from the American Heart Association/American Stroke Association.

            Despite the global impact and advances in understanding the pathophysiology of cerebrovascular diseases, the term "stroke" is not consistently defined in clinical practice, in clinical research, or in assessments of the public health. The classic definition is mainly clinical and does not account for advances in science and technology. The Stroke Council of the American Heart Association/American Stroke Association convened a writing group to develop an expert consensus document for an updated definition of stroke for the 21st century. Central nervous system infarction is defined as brain, spinal cord, or retinal cell death attributable to ischemia, based on neuropathological, neuroimaging, and/or clinical evidence of permanent injury. Central nervous system infarction occurs over a clinical spectrum: Ischemic stroke specifically refers to central nervous system infarction accompanied by overt symptoms, while silent infarction by definition causes no known symptoms. Stroke also broadly includes intracerebral hemorrhage and subarachnoid hemorrhage. The updated definition of stroke incorporates clinical and tissue criteria and can be incorporated into practice, research, and assessments of the public health.
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              Data Resource Profile: The National Health Information Database of the National Health Insurance Service in South Korea

              Data resource basics The National Health Information Database (NHID) is a public database on health care utilization, health screening, socio-demographic variables, and mortality for the whole population of South Korea, formed by the National Health Insurance Service. The population included in the data is over 50 million, and the participation rate in the health screening programs was 74.8% in 2014. The NHID covers data between 2002 and 2014. Those insured by NHI pay insurance contributions and receive medical services from their health care providers. The NHIS, as the single insurer, pays costs based on the billing records of health care providers (Figure 1). To govern and carry out these processes in the NHI, the NHIS built a data warehouse to collect the required information on insurance eligibility, insurance contributions, medical history, and medical institutions. In 2012, the NHIS formed the NHID using information from medical treatment and health screening records and eligibility data from an existing database system. Figure 1. The governance of the National Health Insurance of South Korea. Data collected The eligibility database includes information about income-based insurance contributions, demographic variables, and date of death. The national health screening database includes information on health behaviors and bio-clinical variables. The health care utilization database includes information on records on inpatient and outpatient usage (diagnosis, length of stay, treatment costs, services received) and prescription records (drug code, days prescribed, daily dosage). The long-term care insurance database includes information about activities of daily living and service grades. The health care provider database includes data about the types of institutions, human resources, and equipment. In the NHID, de-identified join keys replacing the personal identifiers are used to interlink these databases. Data resource use Papers published covered various diseases or health conditions like infectious diseases, cancer, cardiovascular diseases, hypertension, diabetes mellitus, and injuries and risk factors such as smoking, alcohol consumption, and obesity. The impacts of health care and public health policies on health care utilization have been also explored since the data include all the necessary information reflecting patterns of health care utilization. Reasons to be cautious First, information on diagnosis and disease may not be optimal for identifying disease occurrence and prevalence since the data have been collected for medical service claims and reimbursement. However, the NHID also collects prescription data with secondary diagnosis, so the accuracy of the disease information can be improved. Second, the data linkage with other secondary national data is not widely available due to privacy issues in Korea. Governmental discussions on the statutory reform of data linkage using the NHID are under way. Collaboration and data access Access to the NHID can be obtained through the Health Insurance Data Service home page (http://nhiss.nhis.or.kr). An ethics approval from the researchers’ institutional review board is required with submission of a study proposal, which is reviewed by the NHIS review committee before providing data. Further inquiries on data use can be obtained by contacting the corresponding author. Funding and competing interests This work was supported by the NHIS in South Korea. The authors declare no competing interests.
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                Author and article information

                Journal
                Epidemiol Health
                Epidemiol Health
                EPIH
                Epidemiology and Health
                Korean Society of Epidemiology
                2092-7193
                2024
                26 December 2023
                : 46
                : e2024003
                Affiliations
                [1 ]Department of Public Health, Yonsei University Graduate School, Seoul, Korea
                [2 ]Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea
                [3 ]Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
                [4 ]Institute for Innovation in Digital Healthcare, Yonsei University, Seoul, Korea
                [5 ]Department of Neurology, Chungbuk National University Hospital, Cheongju, Korea
                [6 ]Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
                [7 ]Department of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
                Author notes
                Correspondence: Hyeon Chang Kim Department of Preventive Medicine, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea E-mail: hckim@ 123456yuhs.ac
                Co-correspondence: Jang-Hyun Baek Department of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, 29 Saemunan-ro, Jongno-gu, Seoul 03181, Korea E-mail: janghyun.baek@ 123456gmail.com
                [*]

                Moon & Seo contributed equally to this work as joint first authors.

                Author information
                http://orcid.org/0000-0002-6305-3033
                http://orcid.org/0000-0001-8873-6570
                http://orcid.org/0000-0002-2895-6835
                http://orcid.org/0000-0002-5034-8422
                http://orcid.org/0009-0007-4390-923X
                http://orcid.org/0000-0003-1851-4993
                http://orcid.org/0000-0002-1306-4105
                http://orcid.org/0000-0001-9815-7652
                http://orcid.org/0000-0001-5750-2616
                http://orcid.org/0000-0002-6733-0683
                http://orcid.org/0000-0001-7867-1240
                Article
                epih-46-e2024003
                10.4178/epih.e2024003
                10928468
                38186243
                2cf6cfc8-fc9e-4345-acc7-ec628aba03a8
                © 2024, Korean Society of Epidemiology

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 9 August 2023
                : 5 December 2023
                Categories
                Special Article

                Public health
                stroke,incidence,case fatality rate
                Public health
                stroke, incidence, case fatality rate

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