Global statistics on alcohol, tobacco and illicit drug use: 2017 status report
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
AIMS: This review provides an up-to-date curated source of information on alcohol, tobacco and illicit drug use and their associated mortality and burden of disease. Limitations in the data are also discussed, including how these can be addressed in the future. METHODS: Online data sources were identified through expert review. Data were obtained mainly from the World Health Organization, United Nations Office on Drugs and Crime and Institute for Health Metrics and Evaluation. RESULTS: In 2015, the estimated prevalence among the adult population was 18.4% for heavy episodic alcohol use (in the past 30 days); 15.2% for daily tobacco smoking; and 3.8, 0.77, 0.37 and 0.35% for past-year cannabis, amphetamine, opioid and cocaine use, respectively. European regions had the highest prevalence of heavy episodic alcohol use and daily tobacco use. The age-standardized prevalence of alcohol dependence was 843.2 per 100 000 people; for cannabis, opioids, amphetamines and cocaine dependence it was 259.3, 220.4, 86.0 and 52.5 per 100 000 people, respectively. High-income North America region had among the highest rates of cannabis, opioid and cocaine dependence. Attributable disability-adjusted life-years (DALYs) were highest for tobacco smoking (170.9 million DALYs), followed by alcohol (85.0 million) and illicit drugs (27.8 million). Substance-attributable mortality rates were highest for tobacco smoking (110.7 deaths per 100 000 people), followed by alcohol and illicit drugs (33.0 and 6.9 deaths per 100 000 people, respectively). Attributable age-standardized mortality rates and DALYs for alcohol and illicit drugs were highest in eastern Europe; attributable age-standardized tobacco mortality rates and DALYs were highest in Oceania. CONCLUSIONS: In 2015 alcohol use and tobacco smoking use between them cost the human population more than a quarter of a billion disability-adjusted life years, with illicit drugs costing further tens of millions. Europeans suffered proportionately more, but in absolute terms the mortality rate was greatest in low- and middle-income countries with large populations and where the quality of data was more limited. Better standardized and rigorous methods for data collection, collation and reporting are needed to assess more accurately the geographical and temporal trends in substance use and its disease burden.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 découle