Associations of cannabis use, tobacco use and incident anxiety, mood, and psychotic disorders: a systematic review and meta-analysis
Notice bibliographique
Résumé
Abstract Importance Traditional observational epidemiological studies have consistently found an association between tobacco use, cannabis use and subsequent mental ill-health. However, the extent to which this association reflects an increased risk of new-onset mental ill-health is unclear and may be biased by unmeasured confounding. Objective To examine the association between cannabis use, tobacco use and risk of incident mood, anxiety, and psychotic disorders, and explore risk of bias. Data Sources CINAHL, Embase, MEDLINE, PsycINFO and ProQuest Dissertation and Theses were searched from inception until November 2022, in addition to supplementary searches. Study Selection Longitudinal studies assessing tobacco use and cannabis use and their association with incident mood, anxiety or psychotic disorders were included. Studies conducted in populations selected on health status (e.g., pregnancy) or other highly-selected characteristics (e.g., incarcerated persons) were excluded. Data Extraction and Synthesis A modified Newcastle Ottawa Scale was used to assess study quality. The confounder matrix and E-Values were used to assess potential bias due to unmeasured confounding. Summary risk ratios (RR) were calculated in random-effects meta-analyses using the generic inverse variance method. Main Outcome(s) and Measure(s) Exposures were measured via self-report and defined through status (e.g., current use) or heaviness of use (e.g., cigarettes per day). Outcomes were measured through symptom-based scales, interviews, registry codes and self-reported diagnosis or treatment. Effect estimates extracted were risk of incident disorders by exposure status. Results Seventy-five out of 27789 records were included. Random effects meta-analysis demonstrated a positive association between tobacco use and mood disorder (RR:1.39, 95%CI:1.30–1.47) and psychotic disorder (RR:3.45, 95%CI:2.63-4.53), but not anxiety disorder (RR:1.21, 95%CI:0.87–1.68). Cannabis use was positively associated with psychotic disorders (RR:3.19, 95%CI:2.07-4.90), but not mood disorders (RR:1.31, 95%CI:0.92-1.86) or anxiety disorders (RR:1.10, 95%CI:0.99-1.22). Confounder matrix and E-value assessment indicated estimates were moderately biased by unmeasured confounding. Conclusions and Relevance This systematic review and meta-analysis presents evidence for a longitudinal, positive association between both substances and incident psychotic disorders and tobacco use and mood disorders. There was no evidence to support an association between cannabis use and common mental health conditions. Existing evidence across all outcomes was limited by inadequate adjustment for potential confounders. Future research should prioritise methods allowing for stronger causal inference, such as Mendelian randomization and evidence triangulation.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,013 | 0,034 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,021 | 0,030 |
| Bibliométrie | 0,010 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».