The burden of headache disorders in the Eastern Mediterranean Region, 1990-2016: findings from the Global Burden of Disease study 2016
Bibliographic record
Abstract
OBJECTIVES: Using the findings of the Global Burden of Disease Study (GBD), we report the burden of primary headache disorders in the Eastern Mediterranean Region (EMR) from 1990 to 2016. METHODS: We modelled headache disorders using DisMod-MR 2.1 Bayesian meta-regression tool to ensure consistency between prevalence, incidence, and remission. Years lived with disability (YLDs) were calculated by multiplying prevalence and disability weight (DW) of migraine and tension-type headache (TTH). We assumed primary headache disorders as non-fatal, so their YLD is equal to disability-adjusted life years (DALYs). RESULTS: Migraine and TTH were the second and twentieth leading causes of YLDs in EMR. Between 1990 and 2016, the absolute YLD numbers of migraine and TTH increased from 2.3 million (95% uncertainty interval (UI): 1.5-3.2) to 4.7 million (95%UI: 3-6.5) and from 383 thousand (95%UI: 240-562) to 816 thousand (95%UI: 516-1221), respectively. During the same period, age-standardised YLD rates of migraine and TTH in EMR increased by 0.7% and 2.5%, respectively, in comparison to a small decrease in the global rates (0.2% decrease in migraine and TTH). The bulk of burden due to headache occurred in the 30-49 year age group, with a peak at ages 35-44 years. The age-standardised YLD rates of both headache disorders were higher in women with female to male ratio of 1.69 for migraine and 1.38 for TTH. All countries of the EMR except for Somalia and Djibouti had higher age-standardised YLD rates for migraine and TTH in compare to the global rates. Libya and Saudi Arabia had the highest increase in age-standardised YLD rates of migraine and TTH, respectively. CONCLUSION: The findings of this study show that primary headache disorders are a major and a growing cause of disability in EMR. Since 1990, burden of primary headache disorders has constantly been higher in EMR compared to rest of the world, which indicates that health systems in EMR must focus further on developing and implementing preventive and management strategies to control headache.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".