The association between social factors and migraine or severe headache in men: a secondary analysis of national population-based studies with machine learning models
Abstract
BACKGROUND: Migraine is recognized as a global public health issue. It is more prevalent among women; therefore, studies focusing solely on migraine in men are scarce. We aimed to investigate the relationship between social factors and migraine or severe headache in men, based on a Chinese national population study and the National Health and Nutrition Examination Survey (NHANES).
METHOD: In 2009, we conducted a population-based survey on headaches, for which 5,041 unrelated individuals were randomly selected and visited in all regions of China. A secondary analysis was performed on the data pertaining to men. Data retrieved from the NHANES between 1999 and 2004 were analyzed alongside the same social factors. Logistic regression was used to analyze the factors affecting men. We compared the predictive performance of six machine learning models: XGBoost, Random Forest, Decision Tree, Logistic Regression, Support Vector Machine, and K-Nearest Neighbors.
RESULTS: Of 2,496 male Chinese participants, 236 (9.5%) were diagnosed with migraine or severe headache. According to the NHANES data, 714 (16.6%) of 4,303 male participants reported migraine or severe headache. Logistic regression of the two studies consistently revealed a positive association between obesity and migraine or severe headache (Chinese participants: odds ratio [OR] = 2.017, p = 0.020; NHANES sample: OR = 1.256, p = 0.038) as well as a negative correlation between increased income and the same condition.…
How strong is the evidence?
Evidence Hub reads this as a secondary / pooled analysis, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 5,041 participants or records.
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