Investigating the Association Between Childhood Physical Abuse and Migraine
Bibliographic record
Abstract
BACKGROUND: Recent clinical and population-based studies suggest that adults who were physically abused as children are more likely to experience migraine than those who were not abused. OBJECTIVES: To investigate the relationship between childhood physical abuse and migraine while controlling for age, race, and gender, in addition to the following potential confounders: adverse childhood conditions; adult socioeconomic indicators; current health behaviors; current stressors; history of physical health conditions, and history of mood and/or anxiety disorders. METHODS: Secondary analysis of the 2005 Canadian Community Health Survey was undertaken using a regional sample of 13,089 men and women from Manitoba and Saskatchewan (response rate = 83.3% and 84.1%, respectively) of which 7.4% (n = 1025) of respondents reported childhood physical abuse. A series of logistic regression models were used to determine the association between abuse and self-report of a health professional diagnosis of migraine. RESULTS: Prevalence of a migraine was almost twice as high for those who reported childhood physical abuse in comparison with those who did not (17.9% vs 8.8%). The crude odds ratio was 2.27 (99% CI = 1.80, 2.86). The odds ratio of migraine was 1.77 (99% CI = 1.39, 2.25) for those who reported childhood physical abuse in comparison with those who did not when only age, gender, and race were adjusted for. When all 6 clusters of potential confounders were included in a final model the odds ratio declined but remained significant at 1.36 (99% CI = 1.04, 1.79). CONCLUSIONS: This study found a stable association between childhood physical abuse and migraine that persisted when 6 clusters of potentially confounding factors were adjusted for. Future research should investigate possible mechanisms which explain the abuse-migraine association.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".