IS THERE AN ASSOCIATION BETWEEN BODY MASS INDEX AND MIGRAINE HEADACHES WITHIN THE CANADIAN POPULATION?
Bibliographic record
Abstract
Introduction Obesity (a body mass index ≥30 kg/m2) and migraine headaches are both chronic conditions that have become increasingly common within the Canadian population. Increasing body mass index (BMI) is associated with increased frequency and severity of migraine headaches, but not its prevalence, such that increasing BMI leads to greater disability by exacerbating migraine symptoms among migraneurs. The association between increasing BMI and the prevalence of migraine headaches, however, has provided inconsistent findings. There is uncertainty as to whether there is an association between increasing BMI and an individual's risk of developing and having this condition. Some studies have found that there is an association, whereas other studies have dismissed such a relationship. There has been little to no Canadian studies conducted to determine the association between increasing BMI and the prevalence of migraines, and the Canadian Community Health Survey (CCHS) dataset has not been used as a source population. Objective To investigate whether increasing BMI (underweight, normal, overweight, obese) was significantly associated with a linear dose-response trend in the prevalence of migraine headaches. It is hypothesized that compared with normal weight, increasing BMI would result in a larger prevalence. Methods A sample population of 113 235 subjects from the 2007–2008 cross-sectional CCHS, Cycle 4.1 was used. Subjects included those who had responded to questions regarding self-reported height, weight and migraine status. Subjects less than 18 years of age, and those who were pregnant, were excluded. Log binomial modelling was used to derive unadjusted and adjusted prevalence ratio (PR) estimates, with their corresponding 95% CI. Population weights and average design effects were incorporated to adjust for the effects of complex survey designs. Results When adjusting for covariates compared with normal weight, the PR for migraines was highest and significant only among the obese, 1.19 (95% CI 1.12 to 1.27), followed by underweight which was not significant, 1.09 (95% CI 0.97 to 1.23), and overweight which was marginally significant, 1.06 (95% CI 1.00 to 1.12). Conclusions Obese and overweight BMI were significantly associated with increased prevalence of migraine headaches. Although a U-shaped pattern was observed with obese and underweight at the extremes, when addressing the non-significant PR estimates for underweight, a resulting linear dose-response trend was present, thus, resulting in the obese having the highest PR followed by overweight and normal weight. Small samples of underweight subjects, various biases, and/or an actual plausible mechanism for underweight and migraine prevalence could have accounted for the high PR estimates for underweight. Additional studies to verify results are warranted.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".