115 research outputs found

    Physiological and cell ultrastructure disturbances in wheat seedlings generated by Chenopodium murale hairy root exudate.

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    Chenopodium murale L. is an invasive weed species significantly interfering with wheat crop. However, the complete nature of its allelopathic influence on crops is not yet fully understood. In the present study, the focus is made on establishing the relation between plant morphophysiological changes and oxidative stress, induced by allelopathic extract. Phytotoxic medium of C. murale hairy root clone R5 reduced the germination rate (24% less than control value) of wheat cv. Nataša seeds, as well as seedling growth, diminishing shoot and root length significantly, decreased total chlorophyll content, and induced abnormal root gravitropism. The R5 treatment caused cellular structural abnormalities, reflecting on the root and leaf cell shape and organization. These abnormalities mostly included the increased number of mitochondria and reorganization of the vacuolar compartment, changes in nucleus shape, and chloroplast organization and distribution. The most significant structural changes were observed in cell wall in the form of amoeboid protrusions and folds leading to its irregular shape. These structural alterations were accompanied by an oxidative stress in tissues of treated wheat seedlings, reflected as increased level of H2O2 and other ROS molecules, an increase of radical scavenging capacity and total phenolic content. Accordingly, the retardation of wheat seedling growth by C. murale allelochemicals may represent a consequence of complex activity involving both cell structure alteration and physiological processes.This is a post-peer-review, pre-copyedit version of an article published in Protoplasma. The final authenticated version is available online at: [http://dx.doi.org/10.1007/s00709-018-1250-0

    Small Interfering RNA Targeted to IGF-IR Delays Tumor Growth and Induces Proinflammatory Cytokines in a Mouse Breast Cancer Model

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    Insulin-like growth factor I (IGF-I) and its type I receptor (IGF-IR) play significant roles in tumorigenesis and in immune response. Here, we wanted to know whether an RNA interference approach targeted to IGF-IR could be used for specific antitumor immunostimulation in a breast cancer model. For that, we evaluated short interfering RNA (siRNAs) for inhibition of in vivo tumor growth and immunological stimulation in immunocompetent mice. We designed 2′-O-methyl-modified siRNAs to inhibit expression of IGF-IR in two murine breast cancer cell lines (EMT6, C4HD). Cell transfection of IGF-IR siRNAs decreased proliferation, diminished phosphorylation of downstream signaling pathway proteins, AKT and ERK, and caused a G0/G1 cell cycle block. The IGF-IR silencing also induced secretion of two proinflammatory cytokines, TNF- α and IFN-γ. When we transfected C4HD cells with siRNAs targeting IGF-IR, mammary tumor growth was strongly delayed in syngenic mice. Histology of developing tumors in mice grafted with IGF-IR siRNA treated C4HD cells revealed a low mitotic index, and infiltration of lymphocytes and polymorphonuclear neutrophils, suggesting activation of an antitumor immune response. When we used C4HD cells treated with siRNA as an immunogen, we observed an increase in delayed-type hypersensitivity and the presence of cytotoxic splenocytes against wild-type C4HD cells, indicative of evolving immune response. Our findings show that silencing IGF-IR using synthetic siRNA bearing 2′-O-methyl nucleotides may offer a new clinical approach for treatment of mammary tumors expressing IGF-IR. Interestingly, our work also suggests that crosstalk between IGF-I axis and antitumor immune response can mobilize proinflammatory cytokines

    Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study

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    Background: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. Methods: Using cognitive testing data and data on functional limitations from Wave A (2001–2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. Results: Our algorithm had a cross-validated predictive accuracy of 88% (86–90), and an area under the curve of 0.97 (0.97–0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3–4) in individuals 70–79, 11% (9–12) in individuals 80–89 years old, and 28% (22–35) in those 90 and older. Conclusions: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

    Diseases, Injuries, and Risk Factors in Child and Adolescent Health, 1990 to 2017: Findings From the Global Burden of Diseases, Injuries, and Risk Factors 2017 Study.

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    Importance:Understanding causes and correlates of health loss among children and adolescents can identify areas of success, stagnation, and emerging threats and thereby facilitate effective improvement strategies. Objective:To estimate mortality and morbidity in children and adolescents from 1990 to 2017 by age and sex in 195 countries and territories. Design, Setting, and Participants:This study examined levels, trends, and spatiotemporal patterns of cause-specific mortality and nonfatal health outcomes using standardized approaches to data processing and statistical analysis. It also describes epidemiologic transitions by evaluating historical associations between disease indicators and the Socio-Demographic Index (SDI), a composite indicator of income, educational attainment, and fertility. Data collected from 1990 to 2017 on children and adolescents from birth through 19 years of age in 195 countries and territories were assessed. Data analysis occurred from January 2018 to August 2018. Exposures:Being under the age of 20 years between 1990 and 2017. Main Outcomes and Measures:Death and disability. All-cause and cause-specific deaths, disability-adjusted life years, years of life lost, and years of life lived with disability. Results:Child and adolescent deaths decreased 51.7% from 13.77 million (95% uncertainty interval [UI], 13.60-13.93 million) in 1990 to 6.64 million (95% UI, 6.44-6.87 million) in 2017, but in 2017, aggregate disability increased 4.7% to a total of 145 million (95% UI, 107-190 million) years lived with disability globally. Progress was uneven, and inequity increased, with low-SDI and low-middle-SDI locations experiencing 82.2% (95% UI, 81.6%-82.9%) of deaths, up from 70.9% (95% UI, 70.4%-71.4%) in 1990. The leading disaggregated causes of disability-adjusted life years in 2017 in the low-SDI quintile were neonatal disorders, lower respiratory infections, diarrhea, malaria, and congenital birth defects, whereas neonatal disorders, congenital birth defects, headache, dermatitis, and anxiety were highest-ranked in the high-SDI quintile. Conclusions and Relevance:Mortality reductions over this 27-year period mean that children are more likely than ever to reach their 20th birthdays. The concomitant expansion of nonfatal health loss and epidemiological transition in children and adolescents, especially in low-SDI and middle-SDI countries, has the potential to increase already overburdened health systems, will affect the human capital potential of societies, and may influence the trajectory of socioeconomic development. Continued monitoring of child and adolescent health loss is crucial to sustain the progress of the past 27 years

    The overlapping burden of the three leading causes of disability and death in sub-Saharan African children

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    Despite substantial declines since 2000, lower respiratory infections (LRIs), diarrhoeal diseases, and malaria remain among the leading causes of nonfatal and fatal disease burden for children under 5 years of age (under 5), primarily in sub-Saharan Africa (SSA). The spatial burden of each of these diseases has been estimated subnationally across SSA, yet no prior analyses have examined the pattern of their combined burden. Here we synthesise subnational estimates of the burden of LRIs, diarrhoea, and malaria in children under-5 from 2000 to 2017 for 43 sub-Saharan countries. Some units faced a relatively equal burden from each of the three diseases, while others had one or two dominant sources of unit-level burden, with no consistent pattern geographically across the entire subcontinent. Using a subnational counterfactual analysis, we show that nearly 300 million DALYs could have been averted since 2000 by raising all units to their national average. Our findings are directly relevant for decision-makers in determining which and targeting where the most appropriate interventions are for increasing child survival. © 2022, The Author(s).Funding text 1: This work was primarily supported by grant OPP1132415 from the Bill & Melinda Gates Foundation. ; Funding text 2: This study was funded by the Bill & Melinda Gates Foundation. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. The non-consortium authors have no competing interests . Competing interests for consortium authors is as follows: Robert Ancuceanu reports receiving consultancy or speaker feeds from UCB, Sandoz, Abbvie, Zentiva, Teva, Laropharm, CEGEDIM, Angelini, Biessen Pharma, Hofigal, AstraZeneca, and Stada. Jacek Jerzy Jozwiak reports personal fees from Amgen, ALAB Laboratories, Teva, Synexus, Boehringer Ingelheim, and Zentiva, all outside the submitted work. Kewal Krishan reports non-financial support from UGC Centre of Advanced Study, CAS II, Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. Walter Mendoza is a Program Analyst in Population and Development at the United Nations Population Fund-UNFPA Country Office in Peru, which does not necessarily endorse or support these findings. Maarten J Postma reports grants and personal fees from MSD, GSK, Pfizer, Boehringer Ingelheim, Novavax, BMS, Seqirus, Astra Zeneca, Sanofi, IQVIA, grants from Bayer, BioMerieux, WHO, EU, FIND, Antilope, DIKTI, LPDP, Budi, personal fees from Novartis, Quintiles, Pharmerit, owning stock options in Health-Ecore and PAG Ltd, and being advisor to Asc Academics, all outside the submitted work. Jasviner A Singh reports personal fees from Crealta/Horizon, Medisys, Fidia, UBM LLC, Trio health, Medscape, WebMD, Clinical Care options, Clearview healthcare partners, Putnam associates, Focus forward, Navigant consulting, Spherix, Practice Point communications, the National Institutes of Health, the American College of Rheumatology, and Simply Speaking, owning stock options in Amarin, Viking, Moderna, Vaxart pharmaceuticals and Charlotte’s Web Holdings, being a member of FDA Arthritis Advisory Committee, the steering committee of OMERACT, an international organization that develops measures for clinical trials and receives arm’s length funding from 12 pharmaceutical companies, and the Veterans Affairs Rheumatology Field Advisory Committee, and acting as Editor and Director of the UAB Cochrane Musculoskeletal Group Satellite Center on Network Meta-analysis, all outside the submitted work. Era Upadhyay has a patent A system and method of reusable filters for anti-pollution mask pending, and a patent A system and method for electricity generation through crop stubble by using microbial fuel cells pending

    Use of multidimensional item response theory methods for dementia prevalence prediction: an example using the Health and Retirement Survey and the Aging, Demographics, and Memory Study.

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    BACKGROUND: Data sparsity is a major limitation to estimating national and global dementia burden. Surveys with full diagnostic evaluations of dementia prevalence are prohibitively resource-intensive in many settings. However, validation samples from nationally representative surveys allow for the development of algorithms for the prediction of dementia prevalence nationally. METHODS: Using cognitive testing data and data on functional limitations from Wave A (2001-2003) of the ADAMS study (n = 744) and the 2000 wave of the HRS study (n = 6358) we estimated a two-dimensional item response theory model to calculate cognition and function scores for all individuals over 70. Based on diagnostic information from the formal clinical adjudication in ADAMS, we fit a logistic regression model for the classification of dementia status using cognition and function scores and applied this algorithm to the full HRS sample to calculate dementia prevalence by age and sex. RESULTS: Our algorithm had a cross-validated predictive accuracy of 88% (86-90), and an area under the curve of 0.97 (0.97-0.98) in ADAMS. Prevalence was higher in females than males and increased over age, with a prevalence of 4% (3-4) in individuals 70-79, 11% (9-12) in individuals 80-89 years old, and 28% (22-35) in those 90 and older. CONCLUSIONS: Our model had similar or better accuracy as compared to previously reviewed algorithms for the prediction of dementia prevalence in HRS, while utilizing more flexible methods. These methods could be more easily generalized and utilized to estimate dementia prevalence in other national surveys

    Global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

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    Background Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980–2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package—a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87–2·04) and has since decreased to 0·95 million deaths (0·91–1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79–3·67) and since then have gradually decreased to 1·94 million (1·63–2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8–39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact

    Mapping geographical inequalities in access to drinking water and sanitation facilities in low-income and middle-income countries, 2000-17

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    Background Universal access to safe drinking water and sanitation facilities is an essential human right, recognised in the Sustainable Development Goals as crucial for preventing disease and improving human wellbeing. Comprehensive, high-resolution estimates are important to inform progress towards achieving this goal. We aimed to produce high-resolution geospatial estimates of access to drinking water and sanitation facilities. Methods We used a Bayesian geostatistical model and data from 600 sources across more than 88 low-income and middle-income countries (LMICs) to estimate access to drinking water and sanitation facilities on continuous continent-wide surfaces from 2000 to 2017, and aggregated results to policy-relevant administrative units. We estimated mutually exclusive and collectively exhaustive subcategories of facilities for drinking water (piped water on or off premises, other improved facilities, unimproved, and surface water) and sanitation facilities (septic or sewer sanitation, other improved, unimproved, and open defecation) with use of ordinal regression. We also estimated the number of diarrhoeal deaths in children younger than 5 years attributed to unsafe facilities and estimated deaths that were averted by increased access to safe facilities in 2017, and analysed geographical inequality in access within LMICs. Findings Across LMICs, access to both piped water and improved water overall increased between 2000 and 2017, with progress varying spatially. For piped water, the safest water facility type, access increased from 40.0% (95% uncertainty interval [UI] 39.4-40.7) to 50.3% (50.0-50.5), but was lowest in sub-Saharan Africa, where access to piped water was mostly concentrated in urban centres. Access to both sewer or septic sanitation and improved sanitation overall also increased across all LMICs during the study period. For sewer or septic sanitation, access was 46.3% (95% UI 46.1-46.5) in 2017, compared with 28.7% (28.5-29.0) in 2000. Although some units improved access to the safest drinking water or sanitation facilities since 2000, a large absolute number of people continued to not have access in several units with high access to such facilities (>80%) in 2017. More than 253 000 people did not have access to sewer or septic sanitation facilities in the city of Harare, Zimbabwe, despite 88.6% (95% UI 87.2-89.7) access overall. Many units were able to transition from the least safe facilities in 2000 to safe facilities by 2017; for units in which populations primarily practised open defecation in 2000, 686 (95% UI 664-711) of the 1830 (1797-1863) units transitioned to the use of improved sanitation. Geographical disparities in access to improved water across units decreased in 76.1% (95% UI 71.6-80.7) of countries from 2000 to 2017, and in 53.9% (50.6-59.6) of countries for access to improved sanitation, but remained evident subnationally in most countries in 2017. Interpretation Our estimates, combined with geospatial trends in diarrhoeal burden, identify where efforts to increase access to safe drinking water and sanitation facilities are most needed. By highlighting areas with successful approaches or in need of targeted interventions, our estimates can enable precision public health to effectively progress towards universal access to safe water and sanitation. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.Peer reviewe

    Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

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    Exclusive breastfeeding (EBF)-giving infants only breast-milk for the first 6 months of life-is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization's Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030.This work was primarily supported by grant no. OPP1132415 from the Bill & Melinda Gates Foundation. Co-authors used by the Bill & Melinda Gates Foundation (E.G.P. and R.R.3) provided feedback on initial maps and drafts of this manuscript. L.G.A. has received support from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Brasil (CAPES), Código de Financiamento 001 and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) (grant nos. 404710/2018-2 and 310797/2019-5). O.O.Adetokunboh acknowledges the National Research Foundation, Department of Science and Innovation and South African Centre for Epidemiological Modelling and Analysis. M.Ausloos, A.Pana and C.H. are partially supported by a grant from the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P4-ID-PCCF-2016-0084. P.C.B. would like to acknowledge the support of F. Alam and A. Hussain. T.W.B. 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. K.Deribe is supported by the Wellcome Trust (grant no. 201900/Z/16/Z) as part of his international intermediate fellowship. C.H. and A.Pana are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNDS-UEFISCDI, project no. PN-III-P2-2.1-SOL-2020-2-0351. B.Hwang is partially supported by China Medical University (CMU109-MF-63), Taichung, Taiwan. M.Khan acknowledges Jatiya Kabi Kazi Nazrul Islam University for their support. A.M.K. acknowledges the other collaborators and the corresponding author. Y.K. was supported by the Research Management Centre, Xiamen University Malaysia (grant no. XMUMRF/2020-C6/ITM/0004). K.Krishan is supported by a DST PURSE grant and UGC Centre of Advanced Study (CAS II) awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M.Kumar would like to acknowledge FIC/NIH K43 TW010716-03. I.L. is a member of the Sistema Nacional de Investigación (SNI), which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación (SENACYT), Panamá. M.L. was supported by China Medical University, Taiwan (CMU109-N-22 and CMU109-MF-118). W.M. is currently a programme analyst in Population and Development at the United Nations Population Fund (UNFPA) Country Office in Peru, which does not necessarily endorses this study. D.E.N. acknowledges Cochrane South Africa, South African Medical Research Council. G.C.P. is supported by an NHMRC research fellowship. P.Rathi acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal, India. Ramu Rawat acknowledges the support of the GBD Secretariat for supporting the reviewing and collaboration of this paper. B.R. acknowledges support from Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal. A.Ribeiro was supported by National Funds through FCT, under the programme of ‘Stimulus of Scientific Employment—Individual Support’ within the contract no. info:eu-repo/grantAgreement/FCT/CEEC IND 2018/CEECIND/02386/2018/CP1538/CT0001/PT. S.Sajadi acknowledges colleagues at Global Burden of Diseases and Local Burden of Disease. A.M.S. acknowledges the support from the Egyptian Fulbright Mission Program. F.S. was supported by the Shenzhen Science and Technology Program (grant no. KQTD20190929172835662). A.Sheikh is supported by Health Data Research UK. B.K.S. acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal for all the academic support. B.U. acknowledges support from Manipal Academy of Higher Education, Manipal. C.S.W. is supported by the South African Medical Research Council. Y.Z. was supported by Science and Technology Research Project of Hubei Provincial Department of Education (grant no. Q20201104) and Outstanding Young and Middle-aged Technology Innovation Team Project of Hubei Provincial Department of Education (grant no. T2020003). The funders of the study had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication. All maps presented in this study are generated by the authors and no permissions are required to publish them

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

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    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. Funding: Bill & Melinda Gates Foundation
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