Faculty Opinions recommendation of Global, regional, and national burden of neurological disorders, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.098 | 0.024 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".