Commentary on Peña <i>et al</i>.: The broader public health relevance of understanding and addressing the alcohol harm paradox
Notice bibliographique
Résumé
Socio-economic inequalities in alcohol-attributable mortality make an important contribution to socio-economic health inequalities overall. A comprehensive approach to reducing socio-economic inequalities in alcohol-related health requires combining the implementation of evidence-based, cost-effective alcohol control policies with broader policy measures that act upon the structural, economic and social root causes of socioeconomic inequalities. The ‘alcohol harm paradox’ is the public health phenomenon that individuals with low socio-economic status (SES) experience greater alcohol-attributable harm despite equal or lower levels of alcohol consumption [1]. The study by Peña et al. [2] is the most recent and potentially most comprehensive effort yet to investigate the role of joint effects between SES and various behavioral risk factors, most importantly alcohol use, as a potential explanation of the alcohol harm paradox. The interaction effects between a low SES and alcohol use that were demonstrated by the authors are not merely useful to explain the alcohol harm paradox; they are probable contributors to severe public health crises of our times, such as the stagnation and decline of life expectancy at birth in the general population of the United States. Seminal research by Case & Deaton [3] has demonstrated that the increases in mortality that are underlying these recent trends are largely driven by an increase in so-called ‘deaths of despair’; that is, deaths from causes that are closely linked to alcohol and drug use (alcohol and drug poisoning, alcoholic liver cirrhosis and suicide). Individuals with low SES are most affected by these increases in mortality. Similarly, inequalities in alcohol-attributable mortality are rising in Europe and constitute an important driver of socio-economic inequality in mortality in many parts of Europe [4]. This underlines the public health importance of understanding and acting upon socio-economic inequalities in alcohol-attributable health above and beyond understanding the alcohol harm paradox. The rise in socio-economic inequalities that can be expected as a consequence of the current COVID-19 pandemic adds urgency to understanding the alcohol harm paradox and the ways in which the high alcohol-attributable burden among those with low SES can be addressed [5]. What options exist to tackle inequalities in alcohol-attributable harm from a public health perspective? Unfortunately, the most cost-effective alcohol control policies, such as taxation, regulation of availability and implementation of screening and brief intervention (SBI) [6], are not well equipped per se to target low SES populations if we do not pay close attention in their implementation [7]. For example, increasing the coverage with SBI may, in fact, exacerbate socio-economic inequalities in health outcomes due to lower health-care access for individuals with low SES [8]. It is therefore important to combine such initiatives with efforts to increase and facilitate health-care access for low SES populations and to ensure that SBI is offered across a wide range of health-care services, including occupational health-care and community health centers. Minimum unit pricing is the policy with the strongest evidence so far on addressing socio-economic inequality in alcohol consumption and alcohol-attributable harm [9, 10]. By setting a floor price on the cheapest alcohol, which is more likely to be purchased by heavy drinkers and drinkers with low SES, minimum unit pricing has been shown to be a promising tool in lowering inequalities in alcohol-attributable harm. Currently, however, only ten countries [11] in the WHO European Region have implemented some form of minimum unit pricing [12]. Even if effective alcohol policies are being implemented, their impact upon health inequality in alcohol-attributable harm is limited, given that the prevalence and average level of drinking are often already lower among those with low SES. Thus, alcohol policies must be accompanied by upstream policy measures that address the root causes of the socio-economic inequalities themselves. Such upstream policies include initiatives for social welfare, universal health-care coverage, quality and equality in education and reducing stigma and social exclusion [13]. Importantly, a ‘health in all policies’ approach should be applied in all policy planning, assessing potential health consequences for the most disadvantaged groups explicitly, rather than focusing upon productivity alone [14]. In conclusion, relying exclusively upon fast-acting downstream interventions that are directed at emerging health consequences will fail to address the underlying causes that give rise to the alcohol-related inequalities in the first place [13]. A comprehensive approach to reducing inequalities in alcohol-related health has to act on several levels, addressing the social determinants of health, relevant behavioral risk factors and health consequences down the line [13]. None. Charlotte Probst: Conceptualization. Carolin Killian: Conceptualization.
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Comment cette classification a été obtenuedéplier
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) | 0,000 | 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 | 0,001 |
| 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».