The prevalence of substance use disorders and substance use in anorexia nervosa: a systematic review and meta-analysis
Notice bibliographique
Résumé
AIM: Individuals with anorexia nervosa (AN) often present with substance use and substance use disorders (SUDs). However, the prevalence of substance use and SUDs in AN has not been studied in-depth, especially the differences in the prevalence of SUDs between AN types [e.g., AN-R (restrictive type) and AN-BP (binge-eating/purge type]. Therefore, this systematic review and meta-analysis aimed to assess the prevalence of SUDs and substance use in AN samples. METHOD: Systematic database searches of the peer-reviewed literature were conducted in the following online databases: MEDLINE, PsycINFO, Embase, and CINAHL from inception to January 2021. We restricted review eligibility to peer-reviewed research studies reporting the prevalence for either SUDs or substance use in individuals with AN. Random-effects meta-analyses using Freeman-Tukey double arcsine transformations were performed on eligible studies to estimate pooled proportions and 95% confidence intervals (CIs). RESULTS: Fifty-two studies met the inclusion criteria, including 14,695 individuals identified as having AN (mean age: 22.82 years). Random pooled estimates showed that substance use disorders had a 16% prevalence in those with AN (AN-BP = 18% vs. AN-R = 7%). Drug abuse/dependence disorders had a prevalence of 7% in AN (AN-BP = 9% vs. AN-R = 5%). In studies that looked at specific abuse/dependence disorders, there was a 10% prevalence of alcohol abuse/dependence in AN (AN-BP = 15% vs. AN-R = 3%) and a 6% prevalence of cannabis abuse/dependence (AN-BP = 4% vs. AN-R = 0%). In addition, in terms of substance use, there was a 37% prevalence for caffeine use, 29% prevalence for alcohol use, 25% for tobacco use, and 14% for cannabis use in individuals with AN. CONCLUSION: This is the most comprehensive meta-analysis on the comorbid prevalence of SUDs and substance use in persons with AN, with an overall pooled prevalence of 16%. Comorbid SUDs, including drugs, alcohol, and cannabis, were all more common in AN-BP compared to AN-R throughout. Therefore, clinicians should be aware of the high prevalence of SUD comorbidity and substance use in individuals with AN. Finally, clinicians should consider screening for SUDs and integrating treatments that target SUDs in individuals with AN. Individuals with anorexia nervosa (AN) may also present with substance use or have a substance use disorder (SUDs). Thus, we conducted a systematic review and meta-analysis to determine the prevalence of substance use and substance use disorders in individuals with AN. We examined published studies that reported the prevalence of either substance use or SUDs in individuals with AN. We found that substance use disorders had a 16% prevalence and that drug abuse/dependence disorders had a prevalence of 7% in those with AN. These rates were much higher in individuals with binge-eating/purging type compared to the restrictive AN. However, many specific substance use disorders and substance use types were low in individuals with AN. Nonetheless, clinicians should be aware of the high prevalence of SUD comorbidity and substance use in individuals with AN.
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 | 0,014 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,019 | 0,038 |
| Bibliométrie | 0,010 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».