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Enregistrement W4388297055 · doi:10.1111/add.16375

Debating Shield <i>et al</i>.'s perspectives on how to formulate alcohol drinking guidelines

2023· article· en· W4388297055 sur OpenAlexaboutno aff
Thomas K. Greenfield

Notice bibliographique

RevueAddiction · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueSubstance Abuse Treatment and Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesNational Institutes of HealthNational Institute on Alcohol Abuse and AlcoholismNational Alcohol Beverage Control Association
Mots-clésMedicineQuality of life (healthcare)PsychologyEnvironmental healthGerontologyNursing

Résumé

récupéré en direct d'OpenAlex

It is premature to make recommendations on new national alcohol guidelines before the evidence of improved uptake is developed. Acute harms follow from bunched drinking or heavy episodic drinking patterns, so daily limits as well as weekly limits are desirable. Shield et al. [1] present an important debate piece undergirding the recently adopted Canadian drinking guidelines. It is valuable to have provided the main rationales for four propositions that the expert panel developed in updating Canada's low-risk drinking guidelines (LRDGs) that are now being implemented in Canada's 2023 Guidance on Alcohol and Health. Two of the propositions are relatively non-controversial: (1) as an indicator of health loss; (2) use of years of life lost (YLL), for which there is higher quality data than disability-adjusted life years (DALYs); and (3) use of a weighted composite risk function versus a cause-specific approach. As regards point (2), a life-course approach without age-specific guidelines, I have some additional concerns, specifically how aging populations might opt for moderate risk if they did not already have cancer (figure 3), given this group often has interacting medications, and younger groups, who might have greater risks from heavy episodic drinking. However, I want to focus primarily on point (4), the risk-zones approach that, in the authors' conclusions, becomes a recommendation. The authors note this is a new LRDG strategy that has not been empirically tested; they provide some examples of similar gradations. One, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition degree of severity of alcohol use disorder (AUD) [2], is not too apt, being aimed at clinicians assessing severity rather than public messaging per se. Although the innovative presentation of risk zones does offer potential to reach individuals with higher levels of drinking and possibly influence them to move down the risk spectrum, it seems premature to make a recommendation for this strategy until there has been opportunity to empirically test, perhaps by a randomized controlled trial or quasi-experiment like the Yukon warning labels study [3], whether the Canadian public actually benefits from this approach. In general, we do not know how effective this innovation will be (contrasted to other LRDG frameworks). The decision to take this approach in Canada seems fine, but I believe recommending it more broadly is premature before marshalling evidence that it works and for whom it is most effective. An additional point regards drinking patterns. The expert panel, by emphasizing average weekly alcohol consumption, implicitly decided that the way alcohol is consumed is less important to health risk. I believe evidence is sufficient that the pattern of drinking, especially bunched into one or two occasions rather than spaced drinking through the week, possibly with meals, affects health outcomes [4, 5]. This may be so even for liver cirrhosis, where chronic drinking dominates, but acute episodes may affect important pathways [6]. Authors note that 21% of Canadians have a heavy episodic drinking pattern and tend to drink outside of meals [1]. It is possible that those now classed in the moderate risk category, with five or six drinks per week, would actually be at high risk for acute harms if they drank this amount in one sitting (not too unlikely); Knupfer [7] identified the myth of the steady drinker years ago, but this remains true; drinking patterns are highly predictive, for example, of AUD [8]. Additionally, a 2015 United States (US) national alcohol survey adjusting for numerous covariates showed that three to four drinks in any day, versus abstention, was associated with higher family and financial harms due to a partner or family member's drinking [9]. Many people obtain their alcohol volume by heavy drinking episodes. The US LRDGs reflect this by separate thresholds for daily drinking and for weekly drinking [10, 11]. Although Shield et al. [1] pay some attention to drinking pattern in the discourse, the decision to not include this in the Canadian LRDGs is not much discussed, and implicitly this reflects a volume-only view of risk. I suspect the expert group may have felt there was insufficient empirical evidence for the role of the pattern, by which the volume was obtained, but with this point I disagree, and at least in the United States, likely also in Canada, multiple important outcomes are associated with exceeding the weekly/daily combined guideline [12]. It may be that having decided on the risk zone framework, introducing daily and weekly amounts was just viewed as “a bridge too far.” A test of both these objectively complex message alternatives is overdue. Funded by National Institute on Alcohol Abuse and Alcoholism (NIAAA) grant P50 AA005595. Opinions are those of the author and do not represent official positions of NIAAA and the National Institutes of Health. T.K.G. has had support from the National Alcohol Beverage Control Association and is a volunteer Member of the Board of Directors of Alcohol Justice. He is a consultant to the University of North Carolina's R01 on alcohol warning labels.

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: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,261
Score d'incertitude au seuil0,459

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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 Opus0,065
Tête enseignante GPT0,352
Écart entre enseignants0,287 · 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'étudeSans objet
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

Citations1
Publié2023
Routes d'admission1
Résumé présentoui

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