Seasonal variation in major depressive episode prevalence in Canada
Notice bibliographique
Résumé
BACKGROUND: The purpose of this paper is to describe variation, over the months of the year, in major depressive episode (MDE) prevalence. This is an important aspect of the epidemiological description of MDE, and one that has received surprisingly little attention in the literature. Evidence of seasonal variation in MDE prevalence has been weak and contradictory. Most studies have sought to estimate the prevalence of seasonal affective disorder using cut-points applied to scales assessing mood seasonality rather than MDE. This approach does not align with modern classification in which seasonal depression is a diagnostic subtype of major depression rather than a distinct category. Also, some studies may have lacked power to detect seasonal differences. We addressed these limitations by examining the month-specific occurrence of conventionally defined MDE and by pooling data from large epidemiological surveys to enhance precision in the analysis. METHOD: Data from two national survey programmes (the National Population Health Survey and the Canadian Community Health Survey) were used, providing ten datasets collected between 1996 and 2013, together including over 500,000. These studies assessed MDE using a short form version of the Composite International Diagnostic Interview (CIDI) for major depression, with one exception being a 2012 survey that used a non-abbreviated version of the CIDI. The proportion of episodes occurring in each month was evaluated using items from the diagnostic modules and statistical methods addressing complex design features of these trials. Overall month-specific pooled estimates and associated confidence intervals were estimated using random effects meta-analysis and a gradient was assessed using a meta-regression model that included a quadratic term. RESULTS: There was considerable sampling variability when the month-specific proportions were estimated from individual survey datasets. However, across the various datasets, there was sufficient homogeneity to justify the pooling of these estimated proportions, producing large gains in precision. Seasonal variation was clearly evident in the pooled data. The highest proportion of episodes occurred in December, January and February and the lowest proportions occurred in June, July and August. The proportion of respondents reporting MDE in January was 70% higher than August, suggesting an association with implications for health policy. The pattern persisted with stratification for age group, sex and latitude. CONCLUSIONS: Seasonal effects in MDE may have been obscured by small sample sizes in prior studies. In Canada, MDE has clear seasonal variation, yet this is not addressed in the planning of services. These results suggest that availability of depression treatment should be higher in the winter than the summer months.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».