MétaCan
Menu
Back to cohort
Record W2472687769 · doi:10.1177/070674370204700407

The Impact of Latitude on the Prevalence of Seasonal Depression

2002· article· en· W2472687769 on OpenAlexaffvenueabout
Anthony Levitt, Michael H. Boyle

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsHealth Sciences CentreMcMaster UniversityUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsDepression (economics)LatitudeDemographyPsychologyGeographyPsychiatryMedicineSociology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.825

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.042
GPT teacher head0.295
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations71
Published2002
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of PsychiatrySame topicClimate Change and Health ImpactsFrench-language works237,207