Global, regional, and national burden of stroke and its risk factors, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019

GBD 2019 Stroke Collaborators

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629 Citations (Scopus)


Background Regularly updated data on stroke and its pathological types, including data on their incidence, prevalence, mortality, disability, risk factors, and epidemiological trends, are important for evidence-based stroke care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) aims to provide a standardised and comprehensive measurement of these metrics at global, regional, and national levels. Methods We applied GBD 2019 analytical tools to calculate stroke incidence, prevalence, mortality, disability-adjusted life-years (DALYs), and the population attributable fraction (PAF) of DALYs (with corresponding 95% uncertainty intervals [UIs]) associated with 19 risk factors, for 204 countries and territories from 1990 to 2019. These estimates were provided for ischaemic stroke, intracerebral haemorrhage, subarachnoid haemorrhage, and all strokes combined, and stratified by sex, age group, and World Bank country income level. Findings In 2019, there were 12·2 million (95% UI 11·0–13·6) incident cases of stroke, 101 million (93·2–111) prevalent cases of stroke, 143 million (133–153) DALYs due to stroke, and 6·55 million (6·00–7·02) deaths from stroke. Globally, stroke remained the second-leading cause of death (11·6% [10·8–12·2] of total deaths) and the third-leading cause of death and disability combined (5·7% [5·1–6·2] of total DALYs) in 2019. From 1990 to 2019, the absolute number of incident strokes increased by 70·0% (67·0–73·0), prevalent strokes increased by 85·0% (83·0–88·0), deaths from stroke increased by 43·0% (31·0–55·0), and DALYs due to stroke increased by 32·0% (22·0–42·0). During the same period, age-standardised rates of stroke incidence decreased by 17·0% (15·0–18·0), mortality decreased by 36·0% (31·0–42·0), prevalence decreased by 6·0% (5·0–7·0), and DALYs decreased by 36·0% (31·0–42·0). However, among people younger than 70 years, prevalence rates increased by 22·0% (21·0–24·0) and incidence rates increased by 15·0% (12·0–18·0). In 2019, the age-standardised stroke-related mortality rate was 3·6 (3·5–3·8) times higher in the World Bank low-income group than in the World Bank high-income group, and the age-standardised stroke-related DALY rate was 3·7 (3·5–3·9) times higher in the low-income group than the high-income group. Ischaemic stroke constituted 62·4% of all incident strokes in 2019 (7·63 million [6·57–8·96]), while intracerebral haemorrhage constituted 27·9% (3·41 million [2·97–3·91]) and subarachnoid haemorrhage constituted 9·7% (1·18 million [1·01–1·39]). In 2019, the five leading risk factors for stroke were high systolic blood pressure (contributing to 79·6 million [67·7–90·8] DALYs or 55·5% [48·2–62·0] of total stroke DALYs), high body-mass index (34·9 million [22·3–48·6] DALYs or 24·3% [15·7–33·2]), high fasting plasma glucose (28·9 million [19·8–41·5] DALYs or 20·2% [13·8–29·1]), ambient particulate matter pollution (28·7 million [23·4–33·4] DALYs or 20·1% [16·6–23·0]), and smoking (25·3 million [22·6–28·2] DALYs or 17·6% [16·4–19·0]). Interpretation The annual number of strokes and deaths due to stroke increased substantially from 1990 to 2019, despite substantial reductions in age-standardised rates, particularly among people older than 70 years. The highest age-standardised stroke-related mortality and DALY rates were in the World Bank low-income group. The fastest-growing risk factor for stroke between 1990 and 2019 was high body-mass index. Without urgent implementation of effective primary prevention strategies, the stroke burden will probably continue to grow across the world, particularly in low-income countries.

Original languageEnglish
Pages (from-to)1-26
Number of pages26
JournalThe Lancet Neurology
Issue number10
Publication statusPublished - 2021

Bibliographical note

Funding Information:
Funding for this study was obtained from the Bill & Melinda Gates Foundation. S Alif would like to acknowledge support from Monash University. S Aljunid would like to acknowledge the Department of Health Policy and Management, Faculty of Public Health, Kuwait University and International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia, for the approval and support to participate in this research project. T Barnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. D Bennett was supported by the National Institute of Health Research (NIHR) Oxford Biomedical Research Centre. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. V Costa acknowledges her grant (SFRH/ BHD/110001/2015), received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006. A Douiri acknowledges support from the National Institute for Health Research (NIHR) Applied Research Collaboration (ARC) South London at King’s College Hospital NHS Foundation Trust and the Royal College of Physicians, as well as the support from the NIHR Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. B Duncan and M Schmidt were supported in part by the Brazilian National Council for Scientific and Technological Development (CNPq, research fellowship) and the Institute for Health Technology Assessment (IATS; 465518/2014-1). N Ghith acknowledges support from a grant from Novo Nordisk Foundation (NNF16OC0021856). A Gialluisi was supported by Fondazione Umberto Veronesi. P Gill is part funded by the NIHR Applied Research Collaboration West Midlands and is NIHR Senior Investigator. The views expressed are those of the author and not necessarily those of the NIHR or the Department of Health and Social Care. V Gupta acknowledges funding support from National Health and Medical Research Council (NHMRC), Australia. S Islam is funded by NHMRC and National Heart Foundation of Australia Fellowships. P Jeemon acknowledges the Wellcome Trust/DBT India Alliance Clinical and Public Health Intermediate Fellowship [IA/CPHI/14/1/501497]. Y Kalkonde is a DBT/Wellcome Trust India Alliance fellow in Public Health (grant number IA/CPHI/14/1/501514). Y Kim was supported by the Research Management Centre, Xiamen University Malaysia (grant number XMUMRF-C6/ITCM/0004). S Koulmane Laxminarayana acknowledges support from Manipal Academy of Higher Education. K Krishan is supported by the UGC Centre of Advanced Study (Phase II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. B Lacey acknowledges support from UK Biobank, University of Oxford. T Lallukka is supported by the Academy of Finland (grant number 330527). S Lorkowski acknowledges institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig (Germany; German Federal Ministry of Education and Research; grant agreement number 01EA1808A). L Mantovani acknowledges support from the Italian Ministry of Health Ricerca Corrente – IRCCS MultiMedica. M Molokhia is supported by the National Institute for Health Research Biomedical Research Center at Guy’s and St Thomas’ National Health Service Foundation Trust and King’s College London. O Odukoya was supported by the Fogarty International Center of the National Institutes of Health under the Award Number K43TW010704. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. M Owolabi is supported by NIH grant SIREN U54 HG007479 under the H3Africa initiative and SIBS Genomics R01NS107900; SIBS Gen Gen R01NS107900-02S1; ARISES R01NS115944; H3Africa CVD Supplement 3U24HG009780-03S5 and CaNVAS 1R01NS114045. A Pana, M Ausloos and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0084. A Raggi, D Sattin and S Schiavolin are supported by a grant from the Italian Ministry of Health (Ricerca Corrente, Fondazione Istituto Neurologico C. Besta, Linea 4—Outcome Research: dagli Indicatori alle Raccomandazioni Cliniche). A Samy acknowledges the support from the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Science and Technology Program (Grant No. KQTD20190929172835662). A Sheikh acknowledges the support of Health Data Research UK. M Tonelli acknowledges support from the David Freeze Chair in Health Research (University of Calgary). B Unnikrishnan acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal. T Wijeratne acknowledges support from the Department of Medicine, University of Rajarata, Sri Lanka. X Xu is supported by the National Heart Foundation of Australia post-doctoral fellowship. S Zaman received a scholarship from the Australian Government research training program (RTP) in support of his academic career. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).

Publisher Copyright:
© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

All Science Journal Classification (ASJC) codes

  • Clinical Neurology


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