Prevalence of Migraine Headache in Taif City, Saudi Arabia
Bibliographic record
Abstract
BACKGROUND: Migraine is a public health problem and it is the third most common cause of disability among individuals below the age of 50. In spite of the multiplicity of the studies concerned with exploring the disease epidemiology and nature worldwide, data from Saudi Arabia are lacking. The aim of this study was to study the prevalence of migraine in Taif city, Saudi Arabia. METHODS: This was a cross-sectional study conducted on 354 individuals in Taif city. Data were collected via a self-administered questionnaire including demographic variables, clinical variables, and therapeutic variables. Data were fed into the computer and analyzed using SPSS software. RESULTS: Among the 354 recruited participants, 54% were females, and 46% were males. Migraine occurred in 89.9% of urban inhabitants. About 24% of migraineurs were unemployed, and 16% were non-working students. Headache occurred in 86.9% of females and 71.6% of males (P = 0.002). Gender was significantly correlated with migraine prevalence (odds ratio (OR) = 0.28). About 47% reported pain score of 4 - 6. Seeking medical advice was encountered in 32.4% of females and 26.6% of males. Nausea occurred in more than one-third of patients before and during headache. Only 31.4% of participants knew about migraine triggers. Family history was found in 64% of participants. CONCLUSIONS: Migraine is prevalent in Taif city. It is more prevalent among females, and among urban areas. Migraine is associated with high rates of unemployment. Most Saudi migraineurs encounter throbbing, moderately severe headache, that does not awake them from sleep. Females report more severe headaches, whereas more men take medications. Nausea is the most common associated symptom with migraine. Only one-third of Saudi migraineurs know about migraine triggers. Family history of migraine is very common among Saudi migraineurs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.025 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".