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Enregistrement W4404084995 · doi:10.1111/add.16704

Commentary on Andreacchi <i>et al</i>.: Policy responses to shifting epidemiological trends in alcohol use in Canada

2024· article· en· W4404084995 sur OpenAlexaffabout
Carolin Kilian, Charlotte Probst

Notice bibliographique

RevueAddiction · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueSubstance Abuse Treatment and Outcomes
Établissements canadiensUniversity of TorontoCentre for Addiction and Mental Health
Organismes subventionnairesNational Institute on Alcohol Abuse and AlcoholismOffice of the National Coordinator for Health Information TechnologyNational Institutes of Health
Mots-clésEpidemiologyMedicinePsychologyEnvironmental health

Résumé

récupéré en direct d'OpenAlex

This commentary examines the public health relevance of age, period and cohort effects in heavy episodic drinking in Canada, focusing on socio-economic inequalities and policy implications. It highlights the paradox between observed socio-economic gradients and persistent disparities in alcohol-attributable harm, and contextualizes these findings within the current Canadian policy environment. In their recent study, Andreacchi and colleagues [1] disentangle epidemiological trends in heavy episodic drinking (HED) by age, period and birth cohort, as well as by sex/gender and socio-economic position (SEP) among Canadian adults. Two indicators of SEP were examined, education and household income, and these yielded two distinct socio-economic patterns. These patterns reflect a heterogeneous picture that is often observed when examining trends in alcohol use by different indicators of SEP and highlight the importance of acknowledging their differences. The observed income gradient in HED prevalence (i.e. higher prevalences with higher incomes) mirrors the financial resources individuals have available for purchasing alcoholic beverages. Compared to those with low incomes, individuals with high incomes spent a lower proportion of their income on each unit of alcohol, making it more affordable. Education, on the other hand, comprises other aspects potentially underlying drinking decisions, such as drinking opportunities, drinking culture or health literacy, leading to a less distinct socio-economic pattern and additional differences by sex/gender. In Canada and elsewhere, low-SEP individuals experience considerably higher alcohol-attributable mortality compared to those with high SEP [2]. This has been observed for both education and income measures [3, 4] and linked to HED [5]. It is thus remarkable that Andreacchi and colleagues did not find corresponding gradients in HED prevalence. On the contrary, HED was found to be lowest in the low-income group, while there was no clear gradient for education. To this end, it should be noted that the HED prevalence presented in this study refers to the entire population. Previous studies, looking at current alcohol users only, found an inverse relationship between SEP and HED [6, 7], indicating a more polarized consumption pattern in low-SEP individuals (i.e. higher prevalences of both abstinence and HED). Moreover, measurement limitations are likely to bias the observed socio-economic patterns. We need to acknowledge that surveys are limited in their ability to reach low-SEP and high-risk drinking groups due to self-selection conditional on alcohol use and SEP, as well as sampling frames excluding very specific populations, such as institutionalized individuals [8]. Andreacchi and colleagues further found a marked drop in the HED prevalence among all income and education levels in the youngest birth cohort (1990–2009), with the low-education group having the lowest prevalence [1]. Although it remains inconclusive whether this trend and shift in education patterns will continue in younger birth cohorts, it is important to explore possible drivers, such as a potential loss of status of drinking alcohol among the youngest cohorts, as has been observed in European countries [9]. However, the declines may be short-lived, given Canada's recent progression towards liberalization of alcohol policies [10]. Due to privatization of alcohol retailing in several provinces [11] and a general trend towards looser pricing regulations [10], Canada's formerly strict alcohol control framework has become increasingly liberal over the past decades. This erosion of alcohol policies may very well be reflected in increasing alcohol-related harms in the near future. Furthermore, despite declines in HED among men and the youngest birth cohort, this drinking pattern remains prevalent in Canada, with one in 10 women and one in five men engaging in HED in 2021 [1]. There are several alcohol policy options available to address HED and the unequal health burden related to it. Pricing policies in particular are not only highly cost-effective in lowering overall alcohol use, but may also result in greater health benefits in low-SEP groups and high-risk alcohol users, who would be most affected by lower alcohol affordability through higher beverage prices [12]. Moreover, beverage-specific excise duties can target alcohol use in high-risk population by levying higher excise taxes on alcoholic beverages that are either most consumed in these groups or known to be linked to greater health risks. For example, spirits have been found to be preferably consumed in low-SEP and high-risk drinking groups [13] and associated with health harms linked to HED [14]. Against Canada's progressive alcohol policy liberalization, policy responses to address individuals engaging in HED and bearing a disproportionate alcohol-attributable health burden are required. Detailed epidemiological trend analysis, as conducted by Andreacchi and colleagues, provides important insights to identify relevant population groups and emerging trends. Carolin Kilian: Conceptualization (lead); writing—original draft (lead); writing-review & editing (equal). Charlotte Probst: Conceptualization (supporting); writing-review & editing (equal). Both authors have equally contributed to the writing during the review & editing process. This article was funded by the US Department of Health and Human Services, National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism R01AA028009. The authors have no financial or other relevant links to companies with an interest in the topic of this article. N/A.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,289
Score d'incertitude au seuil0,417

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,062
Tête enseignante GPT0,355
Écart entre enseignants0,293 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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