Burden of tension-type headache in the Middle East and North Africa region, 1990-2019
Bibliographic record
Abstract
INTRODUCTION: Tension-type headache (TTH) is the most prevalent neurological disorder. As there is a gap in the literature regarding the disease burden attributable to TTH in the Middle East and North Africa (MENA) region, the aim of the present study was to report the epidemiological indicators of TTH in MENA, from 1990 to 2019, by sex, age and socio-demographic index (SDI). METHODS: Publicly available data on the point prevalence, annual incidence and years lived with disability (YLDs) were retrieved from the global burden of disease (GBD) 2019 study for the 21 countries and territories in MENA, between 1990 and 2019. The results were presented with numbers and age-standardised rates per 100000 population, along with their corresponding 95% uncertainty intervals (UIs). RESULTS: In 2019, the age-standardised point prevalence and annual incidence rates for TTH in the MENA region were 24504.5 and 8680.1 per 100000, respectively, which represents a 2.0% and a 0.9% increase over 1990-2019, respectively. The age-standardised YLD rate of TTH in this region in 2019 was estimated to be 68.1 per 100000 population, which has increased 1.0% since 1990. Iran [29640.4] had the highest age-standardised point prevalence rate for TTH, while Turkey [21726.3] had the lowest. In 2019, the regional point prevalence of TTH was highest in the 35-39 and 70-74 age groups, for males and females, respectively. Furthermore, the number of prevalent cases was estimated to be highest in those aged 35-39 and 25-29 years, in both males and females, respectively. Moreover, the burden of TTH was not observed to have a clear association with SDI. CONCLUSIONS: While the prevalence of TTH in the MENA region increased from 1990 to 2019, the incidence rate did not change. In addition, the burden of TTH in MENA was higher than at the global level for both sexes and all age groups. Therefore, prevention of TTH would help alleviate the attributable burden imposed on the hundreds of millions of people suffering from TTH around the region.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".