Comorbidity of Migraine and Mood Episodes in a Nationally Representative Population‐Based Sample
Bibliographic record
Abstract
OBJECTIVE: To examine the lifetime comorbidity of migraine with different combinations of mood episodes: (1) manic episodes alone; (2) depressive episodes alone; (3) manic and depressive episodes; (4) controls with no lifetime history of mood episodes, as well as sociodemographic and clinical correlates of migraine for each migraine-mood episode combination. BACKGROUND: Migraine has been found to be comorbid with bipolar disorder and major depressive disorder in clinical and population-based samples. However, variability in findings across studies suggests that examining mood episodes separately may be fruitful in determining which of these mood episodes are specifically associated with migraine. METHODS: Using a cross-sectional, population-based sample from the Canadian Community Health Survey 1.2 (n = 36,984), sociodemographic and clinical correlates of migraine were examined in each combination of mood episodes as well as controls. Logistic regression analyses controlling for age, sex, and education level compared the lifetime prevalence of migraine (1) between controls and each combination of mood episodes, and then (2) among the different combinations of mood episodes. RESULTS: Migraine comorbidity in all combinations of mood episodes was associated with lower socioeconomic status, earlier onset of affective illness, more anxiety, suicidality and use of mental health resources. Compared with controls, the adjusted odds ratio of having migraine was 2.0 (95% confidence interval [CI] 1.4-2.8) for manic episodes alone, 1.9 (95% CI 1.6-2.1) for depressive episodes alone, and 3.0 (95% CI 2.3-3.9) for subjects with both manic and depressive episodes. Compared with those with manic episodes alone and depressive episodes alone, the odds of having migraine were significantly increased in subjects with both manic and depressive episodes (odds ratio 1.5 vs. manic episodes alone; 1.8 vs. depressive episodes alone). In addition, migraine comorbidity was associated with different correlates depending on the specific combination of mood episodes; in subjects with both manic and depressive episodes, migraine comorbidity was associated with an earlier onset of mental illness, while in subjects with either manic or depressive episodes alone, migraine comorbidity was associated with increased suicidality and anxiety. CONCLUSIONS: Migraine comorbidity appears to delineate a subset of individuals with earlier onset of affective illness and more psychiatric complications, suggesting that migraine assessment in mood disorder patients may be useful as an indicator of potential clinical severity. Differences in the prevalence of migraine as well as sociodemographic and clinical correlates associated with specific combinations of mood episodes underscore the importance of examining this comorbidity by specific type of mood episode.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".