Burden of Ischemic and Hemorrhagic Stroke Across the US From 1990 to 2019

Daniela Renedo; Julian N Acosta; Audrey C Leasure; Richa Sharma; Harlan M Krumholz; Adam de Havenon; Fares Alahdab; Aleksandr Y Aravkin; Zahra Aryan; Till Winfried Bärnighausen; Sanjay Basu; Katrin Burkart; Kaleb Coberly; Michael H Criqui; Xiaochen Dai; Rupak Desai; Samath Dhamminda Dharmaratne; Rajkumar Doshi; Islam Y Elgendy; Valery L Feigin; Irina Filip; Mohamed M Gad; Sherief Ghozy; Nima Hafezi-Nejad; Rizwan Kalani; Ibraheem M Karaye; Adnan Kisa; Vijay Krishnamoorthy; Warren Lo; Tomislav Mestrovic; Ted R Miller; Awoke Misganaw; Ali H Mokdad; Christopher J L Murray; Zuhair S Natto; Amir Radfar; Pradhum Ram; Gregory A Roth; Allen Seylani; Nilay S Shah; Purva Sharma; Aziz Sheikh; Jasvinder A Singh; Suhang Song; Houman Sotoudeh; Dominique Vervoort; Cong Wang; Hong Xiao; Suowen Xu; Ramin Zand; Guido J Falcone; Kevin N Sheth

doi:10.1001/jamaneurol.2024.0190

. 2024 Mar 4;81(4):394–404. doi: 10.1001/jamaneurol.2024.0190

Burden of Ischemic and Hemorrhagic Stroke Across the US From 1990 to 2019

Daniela Renedo ^1,², Julian N Acosta ¹, Audrey C Leasure ¹, Richa Sharma ³, Harlan M Krumholz ^4,^5,⁶, Adam de Havenon ¹, Fares Alahdab ⁷, Aleksandr Y Aravkin ^8,^9,¹⁰, Zahra Aryan ^11,¹², Till Winfried Bärnighausen ^13,¹⁴, Sanjay Basu ^15,¹⁶, Katrin Burkart ^9,¹⁰, Kaleb Coberly ⁹, Michael H Criqui ¹⁷, Xiaochen Dai ^9,¹⁰, Rupak Desai ¹⁸, Samath Dhamminda Dharmaratne ^9,^10,¹⁹, Rajkumar Doshi ²⁰, Islam Y Elgendy ^21,²², Valery L Feigin ^9,^22,²³, Irina Filip ²⁴, Mohamed M Gad ^25,²⁶, Sherief Ghozy ²⁷, Nima Hafezi-Nejad ²⁸, Rizwan Kalani ²⁹, Ibraheem M Karaye ^30,³¹, Adnan Kisa ^32,³³, Vijay Krishnamoorthy ^34,³⁵, Warren Lo ^36,³⁷, Tomislav Mestrovic ^9,³⁸, Ted R Miller ^39,⁴⁰, Awoke Misganaw ^10,⁴¹, Ali H Mokdad ^9,¹⁰, Christopher J L Murray ^9,¹⁰, Zuhair S Natto ^42,⁴³, Amir Radfar ⁴⁴, Pradhum Ram ⁴⁵, Gregory A Roth ^9,^10,⁴⁶, Allen Seylani ⁴⁷, Nilay S Shah ⁴⁸, Purva Sharma ⁴⁹, Aziz Sheikh ⁵⁰, Jasvinder A Singh ^51,⁵², Suhang Song ⁵³, Houman Sotoudeh ⁵⁴, Dominique Vervoort ⁵⁵, Cong Wang ⁵⁶, Hong Xiao ⁵⁷, Suowen Xu ^58,⁵⁹, Ramin Zand ⁶⁰, Guido J Falcone ^1,³, Kevin N Sheth ^1,^2,^3,^✉

¹Department of Neurology, Yale School of Medicine, New Haven, Connecticut

²Department of Neurosurgery, Yale School of Medicine, New Haven, Connecticut

³Yale Center for Brain & Mind Health, Yale School of Medicine, New Haven, Connecticut

⁴Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut

⁵Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut

⁶Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut

⁷Evidence-Based Practice Center, Mayo Clinic Foundation for Medical Education and Research, Rochester, Minnesota

⁸Department of Applied Mathematics, University of Washington, Seattle

⁹Institute for Health Metrics and Evaluation, University of Washington, Seattle

¹⁰Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle

¹¹Brigham and Women’s Hospital, Harvard University, Boston, Massachusetts

¹²Non-communicable Diseases Research Center, Tehran University of Medical Sciences, Tehran, Iran

¹³Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany

¹⁴T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts

¹⁵Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada

¹⁶Department of General Internal Medicine, San Francisco General Hospital, San Francisco, California

¹⁷Department of Family Medicine and Public Health, University of California San Diego, La Jolla

¹⁸Division of Cardiology, Atlanta Veterans Affairs Medical Center, Decatur, Georgia

¹⁹Department of Community Medicine, University of Peradeniya, Peradeniya, Sri Lanka

²⁰Department of Cardiology, St. Joseph’s University Medical Center, Paterson, New Jersey

²¹Division of Cardiovascular Medicine, Gill Heart Institute, University of Kentucky, Lexington

²²National Institute for Stroke and Applied Neurosciences, Auckland University of Technology, Auckland, New Zealand

²³Research Center of Neurology, Moscow, Russia

²⁴Avicenna Medical and Clinical Research Institute, Oak Lawn, Illinois

²⁵Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio

²⁶Gillings School of Global Public Health, University of North Carolina Chapel Hill, Chapel Hill

²⁷Department of Radiology, Mayo Clinic, Rochester, Minnesota

²⁸Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland

²⁹Department of Neurology, University of Washington, Seattle

³⁰School of Health Professions and Human Services, Hofstra University, Hempstead, New York

³¹Department of Anesthesiology, Montefiore Medical Center, Bronx, New York

³²School of Health Sciences, Kristiania University College, Oslo, Norway

³³Department of International Health and Sustainability, Tulane University, New Orleans, Louisiana

³⁴Department of Anesthesiology, Duke University, Durham, North Carolina

³⁵Department of Anesthesiology & Pain Medicine, University of Washington, Seattle

³⁶Department of Pediatrics, Ohio State University, Columbus

³⁷Department of Neurology, Nationwide Children’s Hospital, Columbus, Ohio

³⁸University Centre Varazdin, University North, Varazdin, Croatia

³⁹Pacific Institute for Research & Evaluation, Calverton, Maryland

⁴⁰School of Public Health, Curtin University, Perth, Western Australia, Australia

⁴¹School of Public Health, College of Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia

⁴²Department of Dental Public Health, King Abdulaziz University, Jeddah, Saudi Arabia

⁴³Department of Health Policy and Oral Epidemiology, Harvard University, Boston, Massachusetts

⁴⁴College of Medicine, University of Central Florida, Orlando

⁴⁵Division of Cardiology, UPMC Western Maryland, University of Pittsburgh, Pittsburgh, Pennsylvania

⁴⁶Division of Cardiology, University of Washington, Seattle

⁴⁷National Heart, Lung, and Blood Institute, National Institute of Health, Rockville, Maryland

⁴⁸Department of Medicine (Cardiology), Northwestern University, Chicago, Illinois

⁴⁹Department of Medical Oncology, Kent Hospital, Warwick, Rhode Island

⁵⁰Usher Institute, University of Edinburgh, United Kingdom

⁵¹School of Medicine, University of Alabama at Birmingham, Birmingham

⁵²Medicine Service, US Department of Veterans Affairs (VA), Birmingham, Alabama

⁵³Department of Health Policy and Management, University of Georgia College of Public Health, Athens

⁵⁴Department of Radiology, University of Alabama at Birmingham, Birmingham

⁵⁵Department of Health Policy and Management, Johns Hopkins University, Baltimore, Maryland

⁵⁶Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee

⁵⁷Department of Public Health Science, Fred Hutchinson Cancer Research Center, Seattle, Washington

⁵⁸Department of Endocrinology, University of Science and Technology of China, Hefei, China

⁵⁹Max-Planck-Institute for Heart and Lung Research, Bad Nauheim, Germany

⁶⁰Department of Neurology, Pennsylvania State University College of Medicine, Hershey

Accepted for Publication: January 18, 2024.

Published Online: March 4, 2024. doi:10.1001/jamaneurol.2024.0190

^✉

Corresponding Author: Kevin N. Sheth, MD, Yale Center for Brain & Mind Health, Yale School of Medicine, 15 York St, LLCI Room 1003C, PO Box 208018, New Haven, CT 06520 (kevin.sheth@yale.edu).

Author Contributions: Dr Sheth had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Leasure, de Havenon, Aravkin, Bärnighausen, Burkart, Doshi, Feigin, Ghozy, Hafezi-Nejad, Kisa, Mokdad, Ram, Seylani, P. Sharma, Singh, Falcone, Sheth. Acquisition, analysis, or interpretation of data: Renedo, Acosta, Leasure, R. Sharma, Krumholz, Alahdab, Aryan, Basu, Burkart, Coberly, Criqui, Dai, Desai, Dharmaratne, Doshi, Elgendy, Filip, Gad, Ghozy, Hafezi-Nejad, Kalani, Karaye, Kisa, Krishnamoorthy, Lo, Mestrovic, Miller, Misganaw, Mokdad, Murray, Natto, Radfar, Ram, Roth, Shah, Sheikh, Singh, Song, Sotoudeh, Vervoort, Wang, Xiao, Xu, Zand, Falcone, Sheth. Drafting of the manuscript: Renedo, Leasure, Desai, Doshi, Ghozy, Kisa, Ram, Zand, Falcone, Sheth. Critical review of the manuscript for important intellectual content: Acosta, Leasure, R. Sharma, Krumholz, de Havenon, Alahdab, Aravkin, Aryan, Bärnighausen, Basu, Burkart, Coberly, Criqui, Dai, Desai, Dharmaratne, Doshi, Elgendy, Feigin, Filip, Gad, Ghozy, Hafezi-Nejad, Kalani, Karaye, Kisa, Krishnamoorthy, Lo, Mestrovic, Miller, Misganaw, Mokdad, Murray, Natto, Radfar, Ram, Roth, Seylani, Shah, P. Sharma, Sheikh, Singh, Song, Sotoudeh, Vervoort, Wang, Xiao, Xu, Zand, Falcone, Sheth. Statistical analysis: Renedo, Acosta, Leasure, de Havenon, Aravkin, Aryan, Burkart, Dai, Ghozy, Hafezi-Nejad, Karaye, Kisa, Mokdad, Natto, Xu, Sheth. Obtained funding: Aryan, Misganaw, Mokdad, Sheth. Administrative, technical, or material support: Renedo, Coberly, Kisa, Misganaw, Mokdad, Roth, Shah, Sotoudeh, Xu, Sheth. Supervision: Bärnighausen, Criqui, Elgendy, Gad, Karaye, Misganaw, Mokdad, Murray, P. Sharma, Falcone, Sheth.

Conflict of Interest Disclosures: Dr Acosta reported being an employee of Rad AI outside the submitted work. Dr R. Sharma reported receiving grants from the National Institutes of Health outside the submitted work and having a patent to classify ischemic stroke etiology pending. Dr Krumholz reported receiving grants from National Institutes of Health, American Heart Association, Pfizer, Janssen, Johnson & Johnson, Centers for Disease Control and Prevention, contracts from Centers for Medicare & Medicaid Services through Yale New Haven Hospital, grants from Agency for Healthcare Research and Quality, editorial/consultant/advisor and/or nonfinancial support from Massachusetts Medical Society as coeditor of Journal Watch Cardiology, UpToDate, Eyedentify, F-Prime Consultant, Ensight AI, Element Science, Hugo Health, and served as cofounder of Refactor Health, and Ensight AI outside the submitted work. Dr de Havenon reported receiving grants from National Institutes of Health/National Institute of Neurological Disorders and Stroke and personal fees from Novo Nordisk, Certus, TitinKM, and UpToDate outside the submitted work. Dr Basu reported receiving grants from the National Institutes of Health and personal fees from University of California and Waymark outside the submitted work. Dr Burkart reported receiving grants from the University of Washington and funding from the Bill & Melinda Gates Foundation during the conduct of the study. Dr Coberly reported being a research engineer for the Institute for Health Metrics and Evaluation during the conduct of the study. Dr Dai reported receiving grants from the Bill & Melinda Gates Foundation during the conduct of the study. Drs Filip and Radfar reported being employees of the Avicenna Medical and Clinical Research Institute during the conduct of the study. Dr Roth reported receiving grants from the Bill & Melinda Gates Foundation during the conduct of the study. Dr Singh reported receiving personal fees from Schipher, Crealta/Horizon, Medisys, Fidia, PK Med, Two Labs Inc, Adept Field Solutions, Clinical Care Options, Clearview Healthcare Partners, Putnam Associates, Focus Forward, Navigant Consulting, Spherix, MedIQ, Jupiter Life Science, UBM LLC, Trio Health, Medscape, WebMD, Practice Point Communications, and the National Institutes of Health; consulting fees from the American College of Rheumatology; institutional research support from Zimmer Biomet Holding; food and beverage payments from Intuitive Surgical Inc/Philips Electronics North America; and stock options in Atai Life Sciences, Kintara Therapeutics, Intelligent Biosolutions, Acumen Pharmaceutical, TPT Global Tech, Vaxart Pharmaceuticals, Atyu Biopharma, Adaptimmune Therapeutics, GeoVax Labs, Pieris Pharmaceuticals, Enzolytics Inc, Seres Therapeutics, Tonix Pharmaceuticals Holding Corp, and Charlotte’s Web Holdings Inc outside the submitted work. Dr Sheth reported receiving grants from National Institutes of Health, American Heart Association, Hyperfine; personal fees/monitoring board fees/equity from Astrocyte, CSL Behring, Zoll, Sense, Bexorg, Rhaeos, and Alva; and having a patent for Alva licensed. No other disclosures were reported.

Funding/Support: This work was supported in part by the Bill and Melinda Gates Foundation (GBD); the American Heart Association Medical Student Research Fellowship (Dr Leasure); grants K76AG059992 and R03NS112859 from the National Institutes of Health (Dr Falcone), grant 18IDDG34280056 from the American Heart Association (Dr Falcone), grant P30AG021342 from the Yale Pepper Scholar Award (Dr Falcone), and the Neurocritical Care Society Research Fellowship (Dr Falcone); grants U24NS107215, U24NS107136, RO1NR018335, R03NS112859, and U01NS106513 from the National Institutes of Health (Dr Sheth) and grant 17CSA33550004 from the American Heart Association (Dr Sheth), and grants from Hyperfine, Biogen, and Astrocyte unrelated to this work (Dr Sheth).

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Meeting Presentation: This paper was presented as a poster at the International Stroke Conference 2024 of the American Heart Association; February 7, 2024; Phoenix, Arizona.

Data Sharing Statement: See Supplement 2.

^✉

Corresponding author.

PMCID: PMC10913004 PMID: 38436973

This cross-sectional study investigates the stroke burden trends in the US in 2019 and how they evolved from 1990 to 2019 with a focus on age, sex, and region in the US.

Key Points

Question

What are the stroke burden trends in the US for the year 2019, and how have they evolved from 1990 to 2019 with a focus on factors such as age, sex, and region in the US?

Findings

In this cross-sectional study, in 2019, there were 7.09 million strokes, with 82.7% ischemic in etiology, and although the absolute frequency of stroke and mortality increased, age-standardized rates mostly declined. Hemorrhagic stroke mortality, however, rose significantly, and the overall stroke mortality decline slowed in recent years, with variations by age and region.

Meaning

Results suggest that decreasing age-standardized rates show progress, but the growing stroke burden, especially for hemorrhagic stroke, is a major challenge; disparities in age and region highlight the need for targeted interventions.

Abstract

Importance

Stroke is a leading cause of death and disability in the US. Accurate and updated measures of stroke burden are needed to guide public health policies.

Objective

To present burden estimates of ischemic and hemorrhagic stroke in the US in 2019 and describe trends from 1990 to 2019 by age, sex, and geographic location.

Design, Setting, and Participants

An in-depth cross-sectional analysis of the 2019 Global Burden of Disease study was conducted. The setting included the time period of 1990 to 2019 in the US. The study encompassed estimates for various types of strokes, including all strokes, ischemic strokes, intracerebral hemorrhages (ICHs), and subarachnoid hemorrhages (SAHs). The 2019 Global Burden of Disease results were released on October 20, 2020.

Exposures

In this study, no particular exposure was specifically targeted.

Main Outcomes and Measures

The primary focus of this analysis centered on both overall and age-standardized estimates, stroke incidence, prevalence, mortality, and DALYs per 100 000 individuals.

Results

In 2019, the US recorded 7.09 million prevalent strokes (4.07 million women [57.4%]; 3.02 million men [42.6%]), with 5.87 million being ischemic strokes (82.7%). Prevalence also included 0.66 million ICHs and 0.85 million SAHs. Although the absolute numbers of stroke cases, mortality, and DALYs surged from 1990 to 2019, the age-standardized rates either declined or remained steady. Notably, hemorrhagic strokes manifested a substantial increase, especially in mortality, compared with ischemic strokes (incidence of ischemic stroke increased by 13% [95% uncertainty interval (UI), 14.2%-11.9%]; incidence of ICH increased by 39.8% [95% UI, 38.9%-39.7%]; incidence of SAH increased by 50.9% [95% UI, 49.2%-52.6%]). The downturn in stroke mortality plateaued in the recent decade. There was a discernible heterogeneity in stroke burden trends, with older adults (50-74 years) experiencing a decrease in incidence in coastal areas (decreases up to 3.9% in Vermont), in contrast to an uptick observed in younger demographics (15-49 years) in the South and Midwest US (with increases up to 8.4% in Minnesota).

Conclusions and Relevance

In this cross-sectional study, the declining age-standardized stroke rates over the past 3 decades suggest progress in managing stroke-related outcomes. However, the increasing absolute burden of stroke, coupled with a notable rise in hemorrhagic stroke, suggests an evolving and substantial public health challenge in the US. Moreover, the significant disparities in stroke burden trends across different age groups and geographic locations underscore the necessity for region- and demography-specific interventions and policies to effectively mitigate the multifaceted and escalating burden of stroke in the country.

Introduction

Stroke is a leading cause of death and disability in the US. In 2017, the direct and indirect costs associated with stroke in the US totaled $49.8 billion.¹ When discussing the burden of a disease, it is essential to understand that it encompasses both the incident cases, which are new occurrences, and prevalent cases, which signify the total number of existing instances at a given time. Given the rising prevalence of cardiometabolic risk factors and the aging US population, the burden of both ischemic and hemorrhagic strokes is anticipated to significantly increase.² Population-level health information on stroke incidence, prevalence, mortality, and disability and their trends are important for evidence-based health care planning and identification of specific groups that may benefit from tailored interventions.

The Global Burden of Diseases, Injuries, and Risk Factors (GBD) study is a systematic analysis of global data on the magnitude of health loss due to disease, risk factors, and injuries from 1990 to 2019. The GBD study is the only peer-reviewed, comprehensive assessment of stroke by age, sex, and location that is updated annually.³ Increasing evidence suggests that stroke burden is increasing across the life span, with growing incidence in younger populations. However, these trends have not been studied in a nationally representative US population.^4,5,6,7 We therefore sought to provide estimates for ischemic and hemorrhagic stroke in the US from 1990 to 2019 by age, sex, and state in the GBD 2019 study.

Methods

Study Design

In this cross-sectional study, we conducted a secondary analysis of existing data from the GBD study, which was approved by the University of Washington institutional review board committee. Given the nature of our analysis, which did not involve direct interaction with study participants, obtaining informed consent was not applicable. Any ethical considerations relevant to the original data collection were managed under the protocols of the respective primary studies.⁸

The GBD study has been previously described.^3,9 Briefly, the GBD study is a large international effort to quantify health loss from hundreds of diseases, injuries, and risk factors, so that health systems can be improve and disparities can be eliminated. The GBD study uses available epidemiological data, routinely collected data (vital registration, hospitalizations, and medical claims), and statistical modeling to generate the most accurate estimates of disease burden. We used the GBD study 2019 to estimate the incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) lost due to ischemic and hemorrhagic stroke in the US from 1990 to 2019 and to assess the trends in the burden of stroke over this time period, with a focus on age, sex, and geographic variations. Sources for all inputs can be accessed via the GBD 2019 Data Input Sources Tool.¹⁰ The study is performed in compliance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER) guidelines for reporting health estimates. A full list of data sources used in this analysis can be accessed through the GBD Data Input Results Tool¹¹ and the appendices to the GBD 2019 Stroke capstone publication. We adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines to ensure transparent and complete reporting of our study. To this end, we used the checklists to guide the reporting of our study design, methods, results, and conclusions.¹²

Case Definition

We analyzed a composite of all strokes as well as stroke subtypes (ischemic stroke, intracerebral hemorrhage [ICH], and subarachnoid hemorrhage [SAH]). In the GBD study, stroke was defined according to World Health Organization (WHO) criteria as rapidly developing clinical signs of focal disturbance of cerebral function lasting more than 24 hours or leading to death with no apparent cause other than that of vascular origin. Incident strokes were defined as the occurrence of first-ever stroke based on a clinical diagnosis by a physician using diagnostic imaging according to the WHO criteria described previously. Ischemic strokes were defined as all atherosclerotic and thromboembolic events, excluding transient ischemic attacks (TIAs), that resulted in compromised blood flow to brain tissue and subsequent infarction. Hemorrhagic strokes were defined as all nontraumatic events due to SAH or ICH identified by neuroimaging. ICH was defined as stroke with a focal collection of blood in the brain not due to trauma. SAH was defined as nontraumatic stroke due to bleeding into the subarachnoid space of the brain. Both ischemic and hemorrhagic stroke were ascertained using validated International Classification of Diseases, Ninth (ICD-9) and Tenth (ICD-10) codes (eTable 17 in Supplement 1). GBD estimates of stroke burden are based on strokes considered first ever in a lifetime only.

Subgroups

We evaluated stroke by age group, sex, and geographic location. The age groups used were 15 to 49 years, 50 to 74 years, and 75 years or older. Geographic location was defined by state and US region (Northeast, West, South, and Midwest). The GBD study, as a methodology, does not systematically collect information on race and ethnicity.

Outcomes

We report US-specific crude (millions) and age-standardized estimates of incidence, prevalence, mortality, and DALYs per 100 000 and 95% uncertainty intervals (UIs) and their trends or changes from 1990 and 2019 for all stroke, ischemic stroke, ICH, and SAH. DALYs represent the sum of years of life lost (YLL) prematurely and years lived with disability (YLD), and they can be estimated from life tables, estimates of prevalence, and disability weights. DALYs may be expressed as counts or rates.

Statistical Analysis

Methods used to generate estimates of incidence of stroke, prevalence of stroke, mortality, and DALYs have been described elsewhere.¹³ Estimates of stroke incidence and prevalence were produced by using a broad range of population-representative data sources, including scientific reports of cohorts and registries, population surveys, microdata from registry and cohort studies, and health system administrative data like the Healthcare Cost and Utilization Project (HCUP).¹⁴ Bayesian meta-regression software, MR-BRT (Institute for Health Metrics and Evaluation), was used to adjust for known biases for study-level differences including studies that were purely from administrative databases such as HCUP, studies reporting first-ever and recurrent strokes together, studies that reported aggregated stroke subtypes only, and studies that excluded prehospital stroke death in measurement methods and case definitions.^8,15,16 Epidemiologic state-transition disease modeling software, DisMod-MR (Institute for Health Metrics and Evaluation), was used to estimate estimates of incidence and prevalence of stroke. Mortality for stroke and stroke subtypes was estimated using vital registration data coded to the ICD system. The GBD study methodology generally includes verbal autopsy as a potential data source for aggregated stroke estimates (ie, any stroke) but not for subtype specific stroke estimates due to the limited medical history information available in verbal autopsy instruments with respect to stroke. However, for the US context, no verbal autopsy studies were included in the US due to the presence of more detailed vital registration data. Statistical methods were used to increase the comparability of mortality data sources. DALYs were calculated as the sum of YLL, based on a reference maximum observed life expectancy, and number of YLD based on standardized disability weights for each health state. Population-attributable fractions were calculated independently by risk factor by using risk exposures, estimates of relative risk based on meta-analyses, and theoretical minimum risk levels determined for each risk-outcome pair. Adjustment was made for comorbidity by simulating 40 000 individuals in each age, sex, country, and year exposed to the independent probability of acquiring conditions based on their prevalence. The 95% UIs reported for each estimate used 1000 draws from the posterior distribution of models, reported as the 2.5th and 97.5th values of the distribution. Age standardization was performed via the direct method, applying a global age structure from the year 2019. The latest data analysis was released on October 20, 2020.

Results

Burden of Stroke in the US in 2019

There were 7.09 million prevalent strokes (95% UI, 6.41-7.85) in the US in 2019, of which 4.07 million (57.4%; 95% UI, 3.69-4.49) occurred in women and 3.02 million (42.6%; 95% UI, 2.70-3.40) occurred in men (Table 1). Of all strokes, 5.87 million were ischemic (82.7%; 95% UI, 5.15-6.69). There were 0.66 million prevalent ICHs (95% UI, 0.58-0.76) and 0.85 million prevalent SAHs (95% UI, 0.71-1.01). There were 0.46 million new strokes (95% UI, 0.40 - 0.52) in 2019, of which 0.31 million were ischemic (67.5%; 95% UI, 0.26-0.38). There were 0.07 million incident ICHs (95% UI, 0.06-0.09) and 0.07 million incident SAHs (95% UI, 0.06 - 0.09). Deaths due to stroke totaled 0.19 million (95% UI, 0.17-0.21), of which 0.11 million (95% UI, 0.09-0.12) were in women and 0.08 million (95% UI, 0.07-0.08) were in men. DALYs attributed to stroke totaled 3.83 million (95% UI, 3.47-4.16), of which 2.09 million (95% UI, 1.87-2.31) were in women and 1.72 million (95% UI, 1.58-1.86) were in men.

Table 1. Millions of Incident, Prevalent, and Fatal Cases and Disability-Adjusted Life-Years of All Stroke in the US in 1990 and 2019, With Percentage Changes From 1990 to 2019.

Disease	Sex	Incidence 1990	Incidence 2019	Incidence change, %	Prevalence 1990	Prevalence 2019	Prevalence change, %	Mortality 1990	Mortality 2019	Mortality change, %	DALYs 1990	DALYs 2019	DALYs change, %
All stroke	Both	0.37 (0.33-0.44)	0.46 (0.4-0.52)	21.6 (17.0-26.3)	4.37 (3.9-4.88)	7.09 (6.41-7.85)	62.4 (56.3-69.2)	0.15 (0.14-0.16)	0.19 (0.17-0.21)	23.2 (17.5-30.5)	3.13 (2.9-3.34)	3.83 (3.47-4.16)	22.3 (18.1-27.1)
	Women	0.23 (0.2-0.27)	0.28 (0.24-0.32)	18.4 (13.9-23.4)	2.76 (2.47-3.07)	4.07 (3.69-4.49)	47.7 (41.5-54.3)	0.09 (0.08-0.1)	0.11 (0.09-0.12)	19.2 (12.0-28.1)	1.8 (1.64-1.94)	2.1 (1.87-2.31)	16.8 (12.1-22.3)
	Men	0.14 (0.12-0.16)	0.18 (0.16-0.2)	26.8 (21.5-32.0)	1.61 (1.43-1.82)	3.02 (2.7-3.4)	87.4 (78.7-97.8)	0.06 (0.06-0.06)	0.08 (0.07-0.08)	29.4 (23.8-35.9)	1.33 (1.26-1.4)	1.73 (1.58-1.87)	29.6 (24.2-35.0)
Ischemic stroke	Both	0.27 (0.23-0.34)	0.31 (0.26-0.38)	13.0 (8.1-18.4)	3.68 (3.19-4.23)	5.87 (5.14-6.69)	59.5 (52.3-67.9)	0.1 (0.09-0.11)	0.11 (0.09-0.12)	5.4 (−1.4-14.3)	1.88 (1.7-2.05)	2.06 (1.79-2.31)	9.1 (3.4-14.6)
	Women	0.18 (0.14-0.21)	0.2 (0.16-0.24)	11.6 (6.1-17.3)	2.29 (1.98-2.63)	3.24 (2.84-3.69)	41.0 (33.6-49.1)	0.07 (0.06-0.07)	0.07 (0.06-0.08)	6.5 (−1.5-15.1)	1.14 (1.01-1.25)	1.21 (1.04-1.37)	6.3 (0.8-11.3)
	Men	0.1 (0.08-0.12)	0.11 (0.1-0.14)	15.5 (9.8-21.3)	1.39 (1.2-1.6)	2.64 (2.3-3.03)	90.3 (79.8-103.0)	0.04 (0.04-0.04)	0.04 (0.03-0.04)	3.6 (−3.3-13.3)	0.75 (0.69-0.81)	0.85 (0.74-0.96)	13.5 (5.7-21.2)
ICH	Both	0.05 (0.04-0.06)	0.07 (0.06-0.09)	39.8 (35.3-45.0)	0.41 (0.36-0.47)	0.66 (0.58-0.76)	61.6 (56.7-66.3)	0.04 (0.04-0.04)	0.06 (0.05-0.06)	55.8 (47.7-66.3)	0.83 (0.8-0.86)	1.19 (1.12-1.29)	43.6 (37.4-50.8)
	Women	0.03 (0.02-0.03)	0.04 (0.03-0.04)	36.4 (31.2-42.4)	0.24 (0.21-0.28)	0.4 (0.34-0.45)	63.4 (56.4-69.9)	0.02 (0.02-0.02)	0.03 (0.03-0.03)	50.8 (40.8-64.3)	0.4 (0.38-0.42)	0.56 (0.52-0.61)	39.4 (32.1-48.3)
	Men	0.03 (0.02-0.03)	0.04 (0.03-0.04)	43.4 (38.5-49.2)	0.17 (0.15-0.19)	0.27 (0.23-0.31)	59.0 (54.9-63.5)	0.02 (0.02-0.02)	0.03 (0.03-0.03)	61.2 (50.7-73.0)	0.43 (0.41-0.45)	0.63 (0.6-0.69)	47.5 (39.9-55.9)
SAH	Both	0.05 (0.04-0.06)	0.07 (0.06-0.09)	50.9 (44.9-56.3)	0.5 (0.41-0.59)	0.85 (0.71-1.01)	71.7 (64.9-79.1)	0.01 (0.01-0.01)	0.02 (0.02-0.02)	72.4 (49.8-83.4)	0.41 (0.39-0.44)	0.58 (0.53-0.62)	39.3 (33.6-44.8)
	Women	0.03 (0.03-0.04)	0.05 (0.04-0.05)	41.3 (36.0-46.1)	0.35 (0.29-0.42)	0.61 (0.51-0.72)	71.7 (64.6-79.6)	0.01 (0.01-0.01)	0.01 (0.01-0.01)	46.8 (34.3-59.0)	0.26 (0.24-0.28)	0.33 (0.3-0.36)	28.3 (22.1-35.7)
	Men	0.02 (0.01-0.02)	0.03 (0.02-0.03)	69.3 (61.0-77.4)	0.14 (0.12-0.17)	0.24 (0.2-0.29)	71.4 (63.6-79.1)	0.0 (0.0-0.01)	0.01 (0.01-0.01)	114.7 (62.2-138.2)	0.16 (0.15-0.17)	0.25 (0.22-0.27)	57.3 (41.4-68.2)

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Abbreviations: ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

Trends in the Crude Burden of Stroke in the US From 1990 to 2019

The crude number of incident strokes, prevalent strokes, mortality, and DALYs increased from 1990 to 2019 (Table 1). There was a greater increase in percentage change for all measures in men compared with women and in hemorrhagic stroke compared with ischemic stroke. DALYs attributable to stroke increased 29.6% (95% UI, 24.2%-35.0%) in men vs 16.8% (95% UI, 12.1%-22.3%) in women. The incidence of ischemic stroke increased by 13% (95% UI, 14.2%-11.9%), whereas the incidence of ICH increased by 39.8% (95% UI, 38.9%-39.7%) and SAH by 50.9% (95% UI, 49.2%-52.6%). The number of deaths attributable to ischemic stroke increased by 5.4% (95% UI, 0.4%-10.1%), whereas those for ICH increased by 55.8% (95% UI, 51.6%-62.8%) and SAH by 72.4% (95% UI, 60.4%-72.3%).

Trends in the Age-Standardized Burden of Stroke in the US From 1990 to 2019

Age-standardized stroke incidence, prevalence, mortality, and DALYs declined or remained flat from 1990 to 2019, and the magnitude of change in these measures was similar between men and women (Table 2). For all strokes, there were significant reductions in incidence, deaths, and DALYs but no significant change in prevalence. Interestingly, the prevalence of stroke showed notable fluctuations throughout the period from 1990 to 2019 (Figure 1). Overall, when comparing the data from 1990 with that of 2019, the prevalence of ischemic stroke decreased (−2.1%; 95% UI, −1.2% to −3.0%), and the prevalence of ICH and SAH increased 4.9% (95% UI, 4.5%-5.2%) and 1.4% (95% UI, 2.3%-0.9%), respectively. Incidence, deaths, and DALYs had a larger percentage decrease in ischemic stroke compared with hemorrhagic stroke (Table 2). When evaluating trends in incidence by year, the incidence of ischemic stroke decreased over time but the incidence of ICH and SAH has plateaued since 2000 (Figure 1). Mortality and DALYs for all stroke subtypes declined from 2000 to 2010 but have since plateaued from 2010 to 2019 (Figure 1).

Table 2. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Years Rates (per 100 000 Persons), for All Stroke in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019.

Disease	Sex	Incidence 1990	Incidence 2019	Incidence change, %	Prevalence 1990	Prevalence 2019	Prevalence change, %	Mortality 1990	Mortality 2019	Mortality change, %	DALYs 1990	DALYs 2019	DALYs change, %
All stroke	Both	118.8 (103.9 to 136.83)	86.96 (77.21 to 98.22)	−26.8 (−29.1 to −24.3)	1395.46 (1254.62 to 1547.65)	1388.59 (1259.06 to 1529.65)	−0.5 (−4.1 to 3.6)	45.78 (41.85 to 47.9)	30.76 (27.33 to 33.18)	−32.8 (−35.5 to −29.0)	983.78 (913.69 to 1048.01)	713.87 (648.1 to 777.83)	−27.4 (−30.0 to −24.6)
	Women	127.19 (110.89 to 146.88)	96.04 (84.82 to 109.0)	−24.5 (−26.9 to −21.8)	1541.05 (1388.24 to 1703.11)	1488.75 (1352.86 to 1622.77)	−3.4 (−7.2 to 0.6)	43.28 (38.7 to 45.73)	29.68 (25.72 to 32.6)	−31.4 (−34.8 to −26.5)	955.29 (875.65 to 1031.44)	702.36 (626.63 to 774.08)	−26.5 (−29.4 to −23.2)
	Men	106.39 (93.4 to 123.04)	75.75 (67.56 to 85.36)	−28.8 (−31.6 to −26.2)	1206.22 (1074.73 to 1354.93)	1277.78 (1148.33 to 1432.01)	5.9 (1.2 to 11.1)	48.72 (45.71 to 50.52)	31.51 (28.69 to 33.76)	−35.3 (−38.0 to −32.0)	1015.12 (958.91 to 1069.67)	722.5 (662.3 to 781.59)	−28.8 (−31.8 to −25.8)
Ischemic stroke	Both	85.73 (71.42 to 103.59)	58.25 (48.95 to 69.47)	−32.1 (−34.4 to −29.1)	1156.42 (1009.4 to 1319.1)	1131.87 (997.26 to 1278.89)	−2.1 (−6.5 to 2.9)	29.99 (26.67 to 31.7)	16.59 (14.19 to 18.23)	−44.7 (−47.7 to −40.2)	564.97 (509.19 to 618.06)	360.1 (310.57 to 408.06)	−36.3 (−39.9 to −32.9)
	Women	92.78 (77.08 to 112.01)	66.29 (55.49 to 78.83)	−28.5 (−31.1 to −25.3)	1240.59 (1081.87 to 1411.13)	1152.33 (1011.01 to 1288.48)	−7.1 (−11.8 to −1.9)	28.78 (24.88 to 30.78)	17.0 (14.18 to 18.87)	−40.9 (−44.7 to −36.3)	553.47 (490.55 to 612.57)	369.4 (315.95 to 421.54)	−33.3 (−36.9 to −30.1)
	Men	74.55 (62.02 to 90.71)	48.07 (40.27 to 57.26)	−35.5 (−38.4 to −32.6)	1036.17 (898.95 to 1191.3)	1107.66 (971.66 to 1260.93)	6.9 (1.3 to 13.7)	31.01 (28.71 to 32.44)	15.52 (13.81 to 17.15)	−49.9 (−53.1 to −45.1)	572.93 (527.29 to 618.45)	344.99 (298.84 to 390.0)	−39.8 (−44.0 to −35.6)
ICH	Both	16.46 (13.68 to 19.61)	13.76 (11.43 to 16.47)	−16.4 (−18.0 to −14.7)	139.42 (121.47 to 159.36)	146.19 (126.99 to 167.67)	4.9 (1.4 to 8.4)	11.79 (11.06 to 12.26)	10.34 (9.5 to 11.23)	−12.3 (−16.5 to −6.7)	273.47 (262.37 to 284.38)	231.74 (218.48 to 249.45)	−15.3 (−18.9 to −11.1)
	Women	14.3 (11.79 to 17.08)	12.27 (10.14 to 14.7)	−14.2 (−16.4 to −12.1)	148.85 (129.1 to 170.72)	167.66 (144.1 to 193.12)	12.6 (7.9 to 17.7)	10.05 (9.25 to 10.54)	8.97 (8.13 to 9.88)	−10.8 (−16.3 to −3.7)	233.23 (220.53 to 245.02)	200.67 (186.66 to 216.51)	−14.0 (−18.2 to −8.8)
	Men	19.23 (16.04 to 22.9)	15.4 (12.86 to 18.33)	−19.9 (−21.6 to −18.3)	126.65 (109.84 to 145.54)	122.94 (106.79 to 140.74)	−2.9 (−5.3 to −0.3)	14.24 (13.54 to 14.88)	11.92 (11.04 to 12.96)	−16.2 (−21.5 to −10.1)	323.2 (310.72 to 337.86)	265.96 (251.59 to 288.18)	−17.7 (−21.9 to −13.0)
SAH	Both	16.6 (13.9 to 19.79)	14.95 (12.49 to 17.87)	−10.0 (−12.2 to −7.8)	172.89 (143.75 to 205.12)	175.22 (147.0 to 206.98)	1.4 (−1.8 to 4.8)	4.0 (3.82 to 4.22)	3.83 (3.47 to 4.02)	−4.5 (−13.7 to 0.7)	145.34 (136.93 to 154.46)	122.03 (112.96 to 131.3)	−16.0 (−19.0 to −13.1)
	Women	20.11 (16.83 to 23.76)	17.47 (14.62 to 20.82)	−13.1 (−15.6 to −10.8)	230.17 (190.98 to 274.09)	235.89 (197.88 to 279.69)	2.5 (−1.0 to 6.6)	4.45 (4.2 to 4.63)	3.71 (3.4 to 4.02)	−16.5 (−21.3 to −10.1)	168.6 (156.63 to 180.49)	132.3 (120.36 to 145.8)	−21.5 (−25.0 to −17.1)
	Men	12.61 (10.54 to 15.12)	12.29 (10.27 to 14.78)	−2.6 (−5.5 to 0.3)	107.11 (89.49 to 128.25)	108.28 (91.27 to 129.21)	1.1 (−2.0 to 4.3)	3.48 (3.26 to 4.05)	4.06 (3.24 to 4.39)	16.7 (−11.3 to 29.3)	118.99 (111.71 to 127.35)	111.55 (99.84 to 119.61)	−6.3 (−14.5 to −0.1)

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Abbreviations: ICH, intracerebral hemorrhage; SAH, subarachnoid hemorrhage.

Burden of Stroke in the US by Age Group and Geographic Location

Change in stroke incidence, prevalence, mortality, and DALYs from 1990 to 2019 varied by state and age group (Figure 2 and eTables 1-8 in Supplement 1). The percentage change in age-standardized DALYs attributable to stroke ranged from −8.9% (95% UI, −20.4% to 3.2%) in West Virginia to −42.0% (95% UI, −48.7% to −35.3%) in New York (eTable 1 in Supplement 1). Stroke incidence decreased the most in those aged 50 to 74 years (−34.2%; 95% UI, −37.0% to 31.3%), followed by those 75 years and older (−25.6%; 95% UI, −30.6% to −19.6%), and the least in those aged 15 to 49 years (−5.7%; 95% UI, −8.5% to −3.0%) (eTable 5 in Supplement 1). Stroke incidence declined most in older adults (50-74 years) in coastal areas (decreases up to 3.9% in Vermont) but increased in the youngest age group (15-49 years) in the South and Midwest US (with increases up to 8.4% in Minnesota) (Figure 2 and eTables 18-19 in Supplement 1). DALYs and mortality followed a similar pattern, with decreases seen in older age groups across the US but increases seen in the youngest age group in the South and Midwest. Older age groups in the South and Midwest experienced a smaller percentage reduction DALYs and mortality compared with other geographic regions.

Temporal Trends and Risk Factor Impact on Stroke Subtypes in the US: 1990-2019

In 2019, the predominant cause of deaths across all stroke subtypes (ischemic stroke, ICH, and SAH) was the category including all risk factors, accounting for 0.83 million, 0.5 million, and 0.17 million deaths, respectively (eTables 9-16 in Supplement 1). In the GBD study, the category including all risk factors included 83 topics such as environmental risks like air pollution, occupational hazards, malnutrition, substance use, dietary risks, physical inactivity, and various health metrics like high blood pressure and cholesterol.¹⁷ Summaries for all risk factors can be found online.¹⁸ Other significant contributors included metabolic risks and behavioral risks. DALYs showcased similar patterns, with metabolic risk and high systolic blood pressure being prominent for ischemic stroke and ICH, whereas metabolic risks and high body mass index were significant for SAH. Over the 29-year span, marked shifts in the burden of stroke due to various risk factors were observed. Deaths due to high systolic blood pressure decreased by 18.5% for ischemic stroke but rose by 46.2% for SAH. Concurrently, DALYs related to high body mass index surged, witnessing increases of 39.4% and 38.9% for ischemic and SAH, respectively. For ICH, there was a substantial rise in DALYs associated with high fasting plasma glucose level by 111.5%.

Discussion

We report a comprehensive study of incidence, prevalence, mortality, and DALYs estimates and their trends from 1990 to 2019 for ischemic and hemorrhagic stroke in the US. We found an increase in absolute stroke incidence, prevalence, mortality, and DALYs rates from 1990 to 2019 but a decrease in age-standardized stroke incidence, prevalence, mortality, and DALYs rates over this time. Although significant gains have been made in decreasing age-adjusted stroke incidence, mortality, and DALYs during the study period, recent years reveal a plateau on this decline, which is greater for ischemic stroke than hemorrhagic stroke. This finding contrasts with other studies, which observed a recent reversal in the long-standing decline of stroke death rates in the US, particularly among Hispanic individuals and in the South census region.¹⁹ This variation in trends underscores the complexity of stroke epidemiology and highlights the importance of considering demographic and geographic factors in stroke mortality studies. Our study’s use of the comprehensive methodology in the GBD study, which may differ from standard approaches, could partly explain the differences in observed trends. We also found significant variation in the burden of and trends across the lifespan and by geographic location. Although stroke incidence is decreasing overall, the burden of stroke is increasing in the youngest age group in the South and Midwest US.

This study extends existing estimates of stroke burden in the US. The GBD study is the only comprehensive source of stroke estimates that is updated annually. Prior US population-level estimates of stroke prevalence were extrapolated from the 2013 to 2016 National Health and Nutrition Examination Survey. These data estimated 7 million prevalent strokes in 2016, which is consistent with our 2019 GBD estimate of 7.09 million (95% UI, 6.41-7.85). We also provide updated estimates of the burden of ischemic and hemorrhagic stroke. Prior data from the Greater Cincinnati/Northern Kentucky Stroke Study reported that 87% of prevalent strokes are ischemic, 10% are ICH, and 3% are SAH,^19,20 which differ slightly from our reported estimates of 82% ischemic stroke, 12% ICH, and 6% SAH.

The observed increase in crude stroke burden is largely due to population aging and improved stroke survival. Age is the most powerful risk factor for stroke, with stroke rates doubling each decade after 50 years.²¹ The number of US adults 65 years or older is expected to double over the next 40 years and will have a substantial impact on stroke epidemiology.²² In addition, the burden of hemorrhagic stroke is likely to increase as the numbers of patients with atrial fibrillation taking anticoagulation increases.²³ The impact of an aging population with improved stroke survival leads to an increase in the number of US citizens living with stroke. This growing population of patients is at high risk for recurrent stroke and vascular events; the annual risk of future stroke after a first stroke ranges from 3% to 25% depending on age and event type.²⁴ Public health and prevention efforts in the coming years will require a focus on identification of those most at risk for stroke and aggressive management of vascular risk factors in this population.²⁵

Our study highlights trends in stroke burden over time. Although ischemic stroke incidence has steadily decreased since 1990, several factors have likely contributed to this decline. Enhanced public health campaigns have championed healthier lifestyles, leading to better management of hypertension, a primary modifiable risk for stroke. The wider adoption of antihypertensive and cholesterol-lowering medications has also played a significant role.^26,27,28 ICH incidence has plateaued since 2000 with an uptick in recent years, and SAH incidence has remained flat. This may reflect greater treatment of atrial fibrillation with anticoagulants.² Hypertension may also preferentially contribute to hemorrhagic stroke incidence. A prior GBD study found a global increase in the rate of elevated systolic blood pressure and deaths attributable to elevated blood pressure from 1990 to 2015.²⁵ Of note, contrary to findings in previous studies, the incidence rates of ICH and SAH in our analysis were strikingly similar. This is primarily due to the higher incidence rates of SAH compared with ICH at younger ages, primarily younger than 60 years, in our estimates. The global age structure used to age-standardize estimates in the GBD 2019 study also had an impact on age-standardized incidence and prevalence rates as it is much younger than the population structure of the US. Considering age-specific rates of incidence and prevalence of SAH in comparison with ICH is critical to understanding the differences in disease epidemiology. In this study, elevated blood pressure was associated with more deaths from hemorrhagic stroke than ischemic stroke. Another trend seen in this study was a plateau in progress in stroke mortality and DALYs since 2010.

The stagnation observed in our study’s stroke outcomes could be attributed to several factors. First, it might be linked to advancements in stroke intensive care unit care methodologies established before our study period. Second, the potential impact of tissue plasminogen activator, as suggested by studies like those conducted by Adam de Havenon et al²⁹ also appears to be a significant contributing factor. Lastly, advancements in endovascular thrombectomy procedures, although to a lesser extent, may have also played a role. Collectively, these elements suggest that the trends we observed are likely a result of a multifaceted interplay between tissue plasminogen activator use and systemic improvements in stroke treatment.³⁰

However, the conspicuous increase in hemorrhagic stroke mortality could be reflective of the relative paucity of analogous advancements in the treatment modalities for hemorrhagic strokes. The disparity in therapeutic progress between ischemic and hemorrhagic strokes underscores a critical need for focused research and development in hemorrhagic stroke care, to address the rising mortality and bring about equitable advancements in the management of different stroke subtypes.

Our study also showed disparities in stroke burden by age group and geographic location. In contrast to the widespread decrease in stroke burden measures among older adults, we found an increase in measures of stroke burden in the youngest age group that is most pronounced in the South and Midwest US. These findings are consistent with other studies that show an increasing incidence of stroke in younger and middle-aged persons and a high prevalence of cardiovascular risk factors in this population.^6,7,31 Young adults with stroke represent a population with faster accumulation of cardiovascular risk factors. This increased risk may be due to an interaction of genetics and environmental and lifestyle factors. The presence of geographic disparities in stroke burden supports this theory. Prior data from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study indicate that socioeconomic status, rurality, proximity to stroke centers, proportion of Black residents, and inflammation/infection may all contribute to higher stroke incidence and mortality in the Southern US, also known as the Stroke Belt, compared with other regions.³² Furthermore, individuals in these areas are likely to have multiple overlapping social determinants of health, which has been shown to associate with incidence stroke.³³ Future interventions to reduce stroke burden in younger persons in these areas may require the use of genetics, burden of social determinants of health, and other factors to identify individuals at high risk of cardiovascular disease and to implement specific prevention strategies.

The insights derived from our study offer invaluable guidance for both government and private sectors involved in stroke research, prevention, and management. For government entities, a clear understanding of the evolving stroke burden, especially among younger populations and in specific geographic regions, may inform policymaking, budgetary allocation, and targeted public health campaigns. This ensures that interventions are directed where they are needed most, leading to more efficient use of public health funds and potentially more significant health impacts. For the private sector, particularly pharmaceutical companies and health care practitioners, the findings may aid in tailoring research and development efforts, optimizing treatment modalities, and anticipating patient needs. By understanding the nuances of stroke incidence across age and region, these stakeholders may develop and market interventions that cater specifically to identified high-risk populations. In essence, our study paves the way for a synergistic approach, where government policies and private sector initiatives can align, resulting in a comprehensive, cohesive response to the growing challenges of stroke in the US.

Limitations

Although this study was, to our knowledge, the most comprehensive report of ischemic and hemorrhagic stroke burden in the US, there are several limitations. First, there are general limitations of the GBD study. The accuracy of stroke ascertainment is limited by the data input sources. Administrative data or other sources that rely on ICD codes may be prone to misclassification. Second, we lacked detailed information on stroke characteristics other than stroke type. Studies with greater phenotypic detail are needed to inform the burden of and trends in stroke-by-stroke etiology and severity. Third, the absence of data on the US age structure introduces a potential limitation, impacting the accuracy of the estimates. Finally, although we reported on geographic disparities in stroke burden, we do not have data on race and ethnicity. The intersectionality between geographic location and race and ethnicity must be considered when designing policies and interventions to address stroke disparities.

Conclusions

This cross-sectional analysis highlights a significant shift in the stroke burden within the US, particularly accentuating an uptick among younger age groups in the South and Midwest. As the country prepares for an imminent swell in the aging population coupled with a noticeable plateau in advancements against stroke mortality, it becomes evident that future directions must focus on a multipronged strategy. This involves both embracing precision medicine’s potential and fortifying widespread public health campaigns. As these insights emerge, it is paramount to refine our health care strategies, ensuring targeted resource allocation to regions bearing the most significant burden. In synthesizing these elements, this study underscores the urgency for holistic, actionable insights, propelling us toward a more anticipatory and equitable health care future.

Supplement 1.

eTable 1. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for All Stroke in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by State

eTable 2. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for Ischemic Stroke in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by State

eTable 3. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for Intracerebral Hemorrhage in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by State

eTable 4. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for Subarachnoid Hemorrhage in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by State

eTable 5. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for All Stroke in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by Age Group

eTable 6. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for Ischemic Stroke in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by Age Group

eTable 7. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for Intracerebral Hemorrhage in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by Age Group

eTable 8. Age-Standardized Incidence, Prevalence, Mortality, and Disability-Adjusted Life-Year (DALY) Rates (per 100,000 People), for Subarachnoid Hemorrhage in the US in 1990 and 2019 and the Percentage Change From 1990 to 2019 by Age Group

eTable 9. Age-Standardized Incidence and Impact of All Stroke in the US: A Risk Factor Perspective (1990-2019)

eTable 10. Crude Incidence Rates of Stroke in the US: A Detailed Examination of Risk Factors Across All Age Groups (1990-2019)

eTable 11. Age-Standardized Rates of Ischemic Stroke in the US: An Analysis of Risk Factor Influences (1990-2019)

eTable 12. Crude Incidence Rates of Ischemic Stroke in the US: Comprehensive Risk Factor Analysis Across All Ages (1990-2019)

eTable 13. Age-Standardized Incidence Rates of Intracerebral Hemorrhage in the US: Insights from Risk Factor Influences (1990-2019)

eTable 14. Crude Incidence Rates of Intracerebral Hemorrhage in the US: Comprehensive Analysis of Risk Factors Across All Ages (1990-2019)

eTable 15. Age-Standardized Rates and Risk Factors of Subarachnoid Hemorrhage in the USA

eTable 16. Crude Incidence Rates of Subarachnoid Hemorrhage in the US: In-Depth Examination of Risk Factors Across All Age Groups (1990-2019)

eTable 17. ICD Codes Used in Fatal and Nonfatal Analysis Cerebrovascular Disease

eTable 18. Incidence Change by Location and Age Group

eTable 19. Prevalence Change by Location and Age Group

jamaneurol-e240190-s001.xlsx^{(112.4KB, xlsx)}

Supplement 2.

Data Sharing Statement.

jamaneurol-e240190-s002.pdf^{(74.9KB, pdf)}

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