Optimal Expectations and Limited Medical Testing: Evidence from Huntington Disease: Corrigendum
In: American economic review, Band 106, Heft 6, S. 1562-1565
ISSN: 1944-7981
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In: American economic review, Band 106, Heft 6, S. 1562-1565
ISSN: 1944-7981
In: American economic review, Band 103, Heft 5, S. 1977-2002
ISSN: 1944-7981
Human capital theory predicts that life expectancy will impact human capital attainment. We estimate this relationship using variation in life expectancy driven by Huntington disease, an inherited neurological disorder. We compare investments for individuals who have ex-ante identical risks of HD but differ in disease realization. Individuals with the HD mutation complete less education and job training. The elasticity of demand for college attendance with respect to life expectancy is around 1.0. We relate this to cross-country and over-time differences in education. We use smoking and cancer screening data to test the corollary that health capital responds to life expectancy. (JEL I11, I12, I20, I31, J24)
In: American economic review, Band 103, Heft 2, S. 804-830
ISSN: 1944-7981
We use novel data to study genetic testing among individuals at risk for Huntington disease (HD), a hereditary disease with limited life expectancy. Although genetic testing is perfectly predictive and carries little economic cost, presymptomatic testing is rare. Testing rates increase with increases in ex ante risk of having HD. Untested individuals express optimistic beliefs about their health and make decisions (e.g., retirement) as if they do not have HD, even though individuals with confirmed HD behave differently. We suggest that these facts can be reconciled by an optimal expectations model (Brunnermeier and Parker 2005). (JEL D84, I12)
In: NBER Working Paper No. w17931
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In: NBER Working Paper No. w17629
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In: NBER Working Paper No. w15326
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Public Service Loan Forgiveness (PSLF) was established in 2007 for public sector and nonprofit enterprise employees to pursue educational loan forgiveness. Under PSLF, graduates are offered complete loan forgiveness after 120 qualifying monthly payments while employed at public or nonprofit institutions, including payments made during residency for physicians. In response to concerns that PSLF will heavily subsidize lawyers, doctors, and other professionals, the President's 2017 budget proposes limiting maximum forgiveness. Using data from the Association of American Medical Colleges Graduation Questionnaire (n = 55,905; response rate of 80 %), we found that intended participation in PSLF among medical school graduates grew 20 % per year since 2010. Future primary care physicians intend to use PSLF more than programs that were historically designed to promote primary care, such as the National Health Service Corp (NHSC). The federal government's projected cost of PSLF will reach over $316 million for 2014 graduates (net present value), approximately seven times the annual contributions from the NHSC. The proposed cap will reduce the total anticipated forgiveness by nearly two-thirds and substantially reduce subsidies for physicians. More targeted measures of loan forgiveness could be considered, such as making forgiveness contingent on pursuing specialties that society needs or practicing in shortage areas.
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BackgroundWe estimated U.S. biomedical research funding across therapeutic areas, determined the association with disease burden, and evaluated new drug approvals that resulted from this investment.Methodology/principal findingsWe calculated funding from 1995 to 2005 and totaled Food and Drug Administration approvals in eight therapeutic areas (cardiovascular, endocrine, gastrointestinal, genitourinary, HIV/AIDS, infectious disease excluding HIV, oncology, and respiratory) primarily using public data. We then calculated correlations between funding, published estimates of disease burden, and drug approvals. Financial support for biomedical research from 1995 to 2005 increased across all therapeutic areas between 43% and 369%. Industry was the principal funder of all areas except HIV/AIDS, infectious disease, and oncology, which were chiefly sponsored by the National Institutes of Health (NIH). Total (rho = 0.70; P = .03) and industry funding (rho = 0.69; P = .04) were correlated with projected disease burden in high income countries while NIH support (rho = 0.80; P = .01) was correlated with projected disease burden globally. From 1995 to 2005 the number of new approvals was flat or declined across therapeutic areas, and over an 8-year lag period, neither total nor industry funding was correlated with future approvals.Conclusions/significanceAcross therapeutic areas, biomedical research funding increased substantially, appears aligned with disease burden in high income countries, but is not linked to new drug approvals. The translational gap between funding and new therapies is affecting all of medicine, and remedies must include changes beyond additional financial investment.
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BackgroundWe estimated U.S. biomedical research funding across therapeutic areas, determined the association with disease burden, and evaluated new drug approvals that resulted from this investment.Methodology/principal findingsWe calculated funding from 1995 to 2005 and totaled Food and Drug Administration approvals in eight therapeutic areas (cardiovascular, endocrine, gastrointestinal, genitourinary, HIV/AIDS, infectious disease excluding HIV, oncology, and respiratory) primarily using public data. We then calculated correlations between funding, published estimates of disease burden, and drug approvals. Financial support for biomedical research from 1995 to 2005 increased across all therapeutic areas between 43% and 369%. Industry was the principal funder of all areas except HIV/AIDS, infectious disease, and oncology, which were chiefly sponsored by the National Institutes of Health (NIH). Total (rho = 0.70; P = .03) and industry funding (rho = 0.69; P = .04) were correlated with projected disease burden in high income countries while NIH support (rho = 0.80; P = .01) was correlated with projected disease burden globally. From 1995 to 2005 the number of new approvals was flat or declined across therapeutic areas, and over an 8-year lag period, neither total nor industry funding was correlated with future approvals.Conclusions/significanceAcross therapeutic areas, biomedical research funding increased substantially, appears aligned with disease burden in high income countries, but is not linked to new drug approvals. The translational gap between funding and new therapies is affecting all of medicine, and remedies must include changes beyond additional financial investment.
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Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. ; ROA is funded by the National Institutes of Health (U01HG010273). AAw acknowledges funding support from Department of Science and Technology, Government of India, New Delhi, through INSPIRE Faculty scheme. TBA acknowledges partial funding from the Institute of Medical Research and Medicinal Plant Studies. ABa is supported by the Public Health Agency of Canada. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor Award, funded by the Federal Ministry of Education and Research. MSBS acknowledges support from the Australian Government Research and Training Program scholarship for a PhD degree at the Australian National University, Australia. JJC is supported by the Swedish Heart and Lung Foundation. FCar is supported by the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e a Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020UID/QUI/50006/2013. EC is supported by an Australian Research Council Future Fellowship (FT 140100085). KD is supported by a Wellcome Trust [Grant Number 201900] as part of his International Intermediate Fellowship. EF is supported by the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e a Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020UID/QUI/50006/2013. SMSI is funded by the Institute for Physical Activity and Nutrition (IPAN), Deakin University and received funding from High Blood Pressure Research Council of Australia. YKa is a DBT/Wellcome Trust India Alliance Fellow in Public Health. YJK is supported by the Office of Research and Innovation at Xiamen University Malaysia. BL acknowledges funding from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. WDL is supported in part by U10NS086484 NINDS. SLo is funded by the German Federal Ministry of Education and Research (nutriCARD, grant agreement number 01EA1411A). RML is supported by a National Health and Medical Research Council (NHMRC) of Australia Senior Research Fellowship. AMa and the Imperial College London are grateful for support from the NW London NIHR Collaboration for Leadership in Applied Health Research and Care. JJM is supported by the Danish National Research Foundation (Niels Bohr Professorship), and the John Cade Fellowship (APP1056929) from NHMRC. IMV is supported by the Sistema Nacional de Investigación (Panama). MOO is supported by SIREN U54 U54HG007479 and SIBS Genomics R01NS107900 grants. AMS was supported by a fellowship from the Egyptian Fulbright Mission Program. MMSM acknowledges the support from the Ministry of Education, Science and Technological Development, Republic of Serbia (contract no 175087). AShe is supported by Health Data Research UK. MBS' work on traumatic brain injury is supported by grants NIH U01 NS086090 (PI G Manley) from the National Institutes of Health (NIH) and DoD W81XWH-14–2-0176 (PI G Manley) from the United States Department of Defense. RTS is supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIIIFEDER. AGT was supported by a Fellowship from the NHMRC (Australia; 1042600. KBT acknowledges funding supports from the Maurice Wilkins Centre for Biodiscovery, Cancer Society of New Zealand, Health Research Council, Gut Cancer Foundation, and the University of Auckland. CY acknowledges support from the National Natural Science Foundation of China (grant number 81773552) and the Chinese NSFC International Cooperation and Exchange Program (grant number 71661167007).
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Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. ; Bill & Melinda Gates Foundation
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The Parkinson's Disease Digital Biomarker Challenge was funded by the Robert Wood Johnson Foundation and the Michael J. Fox Foundation. Data were contributed by users of the Parkinson mPower mobile application as part of the mPower study developed by Sage Bionetworks and described in Synapse [https://doi.org/10.7303/syn4993293].Resources and support for J.S. were provided by Elder Research, an AI and Data Science consulting agency. M.D. was supported by NIH NIGMS Bioinformatics Training Grant (5T32GM070449-12). J.F.D. was supported by a postdoctoral fellowship from the Canadian Institutes of Health Research. L.L.E. reports grants from the European Research Council ERC (677943), European Union's Horizon 2020 research and innovation programme (675395), Academy of Finland (296801, 304995, 310561 and 314443), and Sigrid Juselius Foundation, during the conduct of the study. EG1 acknowledges the funding support by the Fonds Nationale de la Recherche (FNR) Luxembourg, through the National Centre of Excellence in Research (NCER) on Parkinson's disease (I1R-BIC-PFN-15NCER), and as part of the grant project PD-Strat (INTER/11651464). M.K.J. was supported by Alfred Kordelin Foundation. J.J. is supported by UNSW Sydney Electronic Practice Based Research Network (ePBRN) and Translational Cancer Research Network (TCRN) programs. D.L. is supported in part by the University of Rochester CTSA award number UL1 TR002001 from the National Center for Advancing Translational Sciences of the National Institutes of Health. PS2 is supported by the Swiss National Science Foundation (SNSF) project No. 167302 within the National Research Program (NRP) 75 "Big Data". P.S. is an affiliated PhD fellow at the Max Planck ETH Center for Learning Systems. Y.G. is supported by NIH R35GM133346, NSF#1452656, Michael J. Fox Foundation #17373, American Parkinson Disease Association AWD007950. Cohen Veterans Bioscience contributed financial support to Early Signal Foundation's costs (U.R., C.E., and D.B.). ; Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex data into so-called digital biomarkers requires complicated analytical approaches, and validating these biomarkers requires sufficient data and unbiased evaluation methods. Here we describe the use of crowdsourcing to specifically evaluate and benchmark features derived from accelerometer and gyroscope data in two different datasets to predict the presence of PD and severity of three PD symptoms: tremor, dyskinesia, and bradykinesia. Forty teams from around the world submitted features, and achieved drastically improved predictive performance for PD status (best AUROC = 0.87), as well as tremor- (best AUPR = 0.75), dyskinesia- (best AUPR = 0.48) and bradykinesia-severity (best AUPR = 0.95). ; Robert Wood Johnson Foundation (RWJF) Michael J. Fox Foundation NIH NIGMS Bioinformatics Training Grant 5T32GM070449-12 Canadian Institutes of Health Research (CIHR) European Research Council (ERC) European Commission 677943 European Union's Horizon 2020 research and innovation programme 675395 Academy of Finland 296801 304995 310561 314443 Sigrid Juselius Foundation Fonds Nationale de la Recherche (FNR) Luxembourg, through the National Centre of Excellence in Research (NCER) on Parkinson's disease I1R-BIC-PFN-15NCER project PD-Strat INTER/11651464 Alfred Kordelin Foundation UNSW Sydney Electronic Practice Based Research Network (ePBRN) program UNSW Translational Cancer Research Network (TCRN) program United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Center for Advancing Translational Sciences (NCATS) UL1 TR002001 Swiss National Science Foundation (SNSF) 167302 United States Department of Health & Human Services National Institutes of Health (NIH) - USA R35GM133346 National Science Foundation (NSF) 1452656 Michael J. Fox Foundation 17373 American Parkinson Disease Association AWD007950 Cohen Veterans Bioscience
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In: Feigin , V L , Nichols , E , Alam , T , Bannick , M S , Beghi , E , Blake , N , Culpepper , W J , Dorsey , E R , Elbaz , A , Ellenbogen , R G , Fisher , J L , Fitzmaurice , C , Giussani , G , Glennie , L , James , S L , Johnson , C O , Kassebaum , N J , Logroscino , G , Marin , B , Mountjoy-Venning , W C , Nguyen , M , Ofori-Asenso , R , Patel , A P , Piccininni , M , Roth , G A , Steiner , T J , Stovner , L J , Szoeke , C E I , Theadom , A , Vollset , S E , Wallin , M T , Wright , C , Zunt , J R , Abbasi , N , Abd-Allah , F , Abdelalim , A , Abdollahpour , I , Aboyans , V , Abraha , H N , Acharya , D , Adamu , A A , Adebayo , O M , Adeoye , A M , Adsuar , J C , Afarideh , M , Agrawal , S , Ahmadi , A , Ahmed , M B , Aichour , A N , Pillay , J D & GBD 2016 Neurology Collaborators 2019 , ' Global, regional, and national burden of neurological disorders, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016 ' , The Lancet Neurology , vol. 18 , no. 5 , pp. 459-480 . https://doi.org/10.1016/S1474-4422(18)30499-X
Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding: Bill & Melinda Gates Foundation.
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Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their agestandardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. ; publishedVersion ; © The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
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In: The Lancet Neurology--1474-4422--1474-4465 Vol. 18 Issue. 5 No. pp: 459-480
Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding: Bill & Melinda Gates Foundation.
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