The Impact of Latitude on the Prevalence of Seasonal Depression
Bibliographic record
Abstract
Background: This study sought to determine whether the prevalence of the seasonal subtype of major depression (SAD) in the community varied as a function of latitude. Methods: Random telephone numbers were generated across 8 degrees of latitude (41.5 °N to 49.5°N) for the province of Ontario. Eight strata of 1 degree each were sampled equally throughout a 12-month period. Using a validated and structured diagnostic interview, we interviewed by telephone respondents over 20 years of age who had lived in the region for 3 years or more. We evaluated patterns of symptom change across seasons to establish a diagnosis of SAD according to DSM-IV criteria. Results: Of the 2078 households that were assessed for eligibility, 1605 (77%) completed the interview. The crude prevalence of lifetime SAD was 2.6% (95% CI, 1.9 to 3.5). There was no impact of latitude on prevalence of either major depression or the seasonal subtype across the 8 strata, although the global measure of the severity of seasonal change in mood was significantly negatively correlated with latitude. Conclusions: SAD is a common subtype of major depression in Ontario, but there is no evidence to support an increase in prevalence with increasing latitude. Contexte: Cette étude visait à déterminer si la prévalence du caractère saisonnier de la dépression majeure (DMS) dans la communauté variait selon la latitude. Méthodes: Des numéros de téléphone aléatoires ont été fournis sur 8 degrés de latitude (de 41,5°N. à 49,5°N.) dans la province de l'Ontario. Huit bandes de 1 degré chacune ont été échantillonnées également sur une période de 12 mois. À l'aide d'une entrevue diagnostique validée et structurée, nous avons interviewé par téléphone des répondants âgés de plus de 20 ans qui habitaient la région depuis 3 ans ou plus. Nous avons évalué les changements des modèles de symptômes selon les saisons pour établir un diagnostic de DMS selon les critères du DSM-IV. Résultats: Sur les 2 078 ménages admissibles, 1 605 (77 %) ont terminé l'entrevue. La prévalence brute de la DMS à vie était de 2,6 % (95 % IC, 1,9 à 3,5). La latitude n'influait pas sur la prévalence de la dépression majeure ou du caractère saisonnier dans les 8 bandes, bien que la mesure globale de la sévérité du changement saisonnier de l'humeur ait indiqué une corrélation négative significative à la latitude. Conclusions: La dépression majeure saisonnière est un sous-type répandu de la dépression majeure en Ontario, mais aucune preuve ne soutient une augmentation de la prévalence parallèle à l'accroissement de la latitude.
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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 | 0.001 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".