The association between major depressive disorder and cannabis use disorder: A meta-analysis and meta-regression analysis.
Pini Alemar et al.·Journal of psychiatric researchImpact 3.0
UnklarGRADEModerat1 Zitate
Stichprobek = 55 Studien n = 3.279.774 Pat.
EndpunktKomorbide Prävalenz
Verblindungunklar
DesignMeta-Analyse
”Kernaussage
Meta-Analyse zeigt starke bidirektionale Assoziation zwischen Major Depression und Cannabisstörung (MDD-Prävalenz bei CUD: 19-22%, CUD-Prävalenz bei MDD: 4,6-28,5% je nach Setting).
Zusammenfassung
Meta-Analyse zur bidirektionalen Assoziation zwischen Major Depression (MDD) und Cannabis Use Disorder (CUD); k=55 Studien, n=3.279.774 Teilnehmende (454.547 mit CUD, 112.328 mit MDD). Aktuelle MDD-Prävalenz bei CUD-Patienten: 19,24% (psychiatrische Stichproben) bzw. 21,65% (Community-Stichproben). Aktuelle CUD-Prävalenz bei MDD-Patienten: 28,45% (psychiatrisch) vs. 4,61% (Community). Starke bidirektionale Komorbidität über verschiedene Settings hinweg; kein Publikationsbias (Egger-Test).
P
PopulationPersonen mit Cannabis-Use-Disorder (CUD) oder Major Depressive Disorder (MDD), gepoolt n=3.279.774 (davon 454.547 mit CUD, 112.328 mit MDD)
I
InterventionCannabis-Use-Disorder (CUD) als Exposition/Komorbidität
O
OutcomeAktuelle MDD-Prävalenz bei CUD: psychiatrische Stichproben 19,24%, Gemeindestichproben 21,65%; aktuelle CUD-Prävalenz bei MDD: psychiatrische Stichproben 28,45%, Gemeindestichproben 4,61%
Vertrauen in die Evidenz
Sehr niedrigNiedrigModeratHoch
Moderat
Dritte von vier GRADE-Stufen, die Effektschätzung ist wahrscheinlich verlässlich.
Herabgestuft wegen
Publikationsbias
Qualitätsprofil
Größe★★★★★
Verblindung—
Effektstärke—
Zitate / Jahr★★★★★
Autoren
Pini Alemar J, Pozzolo Pedro MO, Leopoldo K, Mandaji JVG, Gimenes GK, Blaas IK, Torales J, Ventriglio A, Castaldelli-Maia JM
Objective: Major Depressive Disorder (MDD) and Cannabis Use Disorder (CUD) frequently co-occur, yet prevalence estimates vary widely across settings. This meta-analysis updates the evidence on the bidirectional association between MDD and CUD, emphasizing current-diagnosis subgroups, which are the most clinically relevant.
Methods: Following PRISMA and MOOSE guidelines, we systematically searched PubMed, Google Scholar, and SciELO. Random-effects models estimated current-diagnosis prevalence of MDD among individuals with CUD and of CUD among individuals with MDD. Subgroup analyses differentiated psychiatric and community samples. Sensitivity analyses (leave-one-out) and Egger's tests assessed robustness and publication bias. Meta-regressions evaluated demographic, methodological, and geographic moderators.
Results: In total, 55 studies comprising 3,279,774 individuals were included (454,547 and 112,328 living with CUD and MDD, respectively). Current MDD prevalence among individuals with CUD was elevated in both psychiatric samples (19.24%) and community samples (21.65%), indicating consistent comorbidity across settings. Current CUD prevalence among individuals with MDD showed stronger contextual variation, being substantially higher in psychiatric populations (28.45%) compared with community samples (4.61%). Sensitivity analyses demonstrated stable estimates across model specifications, although psychiatric samples exhibited greater variance. Studies with older populations and using ICD-10 (compared to DSM) presented higher MDD prevalence among individuals living with CUD in meta-regression models. Egger's tests revealed no consistent evidence of publication bias.
Conclusion: Current-diagnosis estimates highlight a strong and clinically meaningful bidirectional association between MDD and CUD. Differences between psychiatric and community samples-especially the markedly higher current CUD prevalence in patients with MDD-underscore the need for systematic screening across treatment settings. Future work should improve diagnostic differentiation, particularly regarding the overlap between depressive symptoms and cannabis withdrawal.