ANOTHER EXAMPLE OF AN ILLICIT CIGARETTE MARKET: A STUDY OF PSYCHIATRIC PATIENTS IN TORONTO, ONTARIO
Notice bibliographique
Résumé
Tobacco taxation is a key mechanism for reducing smoking consumption and prevalence in the general population. Few studies, however, have acknowledged the disproportionately heavy tobacco tax burden placed upon some groups—usually poor, marginalized populations—in the drive for population-based public health goals.1 Shelley et al.2 recently examined the relations between a large tax increase in New York State and the development of a pervasive, illicit cigarette market in a low-income minority community and described the financial burden of smoking among the poor who had not quit. Our letter extends these qualitative findings in 2 ways: by examining similar issues in a different marginalized, low-income population—psychiatric patients in one of Canada’s largest psychiatric hospitals—and by quantifying the relative magnitude of illicit cigarette consumption in this population. Approximately 60% to 80% of people with schizophrenia and other severe mental illnesses smoke cigarettes3,4—a rate of roughly 4 times higher than that of the general population in Canada.5 Smoking plays an important role in the significantly higher rates of coronary heart disease morbidity and mortality found among people with severe mental illnesses, and coronary heart disease screening and smoking-cessation programs are much needed for this population.6 Our study involved the collection of cigarette butts from 3 sites in Toronto, Ontario: a 436-bed inpatient psychiatric hospital (where 70–75% of the patients have a primary diagnosis of schizophrenia), an addiction and mental health research and outpatient facility, and a large general hospital. In addition, a garbage audit was performed at the inpatient psychiatric facility to extract cigarette packages from 1 week’s worth of garbage. The collected cigarette butts were then sorted according to their filter-tip logos. In Ontario, an unbranded cigarette filter almost always indicates an illicit brand. The inpatient psychiatric hospital had a dramatically higher rate of “unbranded” cigarette butts: 54% versus 16% at the research facility and 6% at the general hospital site (Figure 1 ▶). The garbage audit resulted in the extraction of 320 cigarette packages. Approximately 80% of the packages were from illicit tobacco brands—a rate dramatically higher than that found in a recent, city-wide garbage audit in Toronto.7 FIGURE 1— Patterns of branding on cigarette butts collected at an inpatient psychiatric hospital (n = 1288 butts), an addiction and mental health research and outpatient treatment facility (n = 1271 butts), and a general hospital (n = 1784 butts). Similar to the findings of Shelley et al., our study demonstrated that cigarette taxation policies appear to place a disproportionate burden on some marginalized groups. As a result, it is important to assess and ensure principles of taxation equity for such populations,8 especially given that higher cigarette prices may paradoxically increase the availability of cheap (but illicit) cigarettes and undermine smoking-related interventions.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,005 |
| Études des sciences et des technologies | 0,009 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».