The contribution of unrecorded alcohol to health harm
Notice bibliographique
Résumé
We thank Drs Lachenmeier & Walch 1 for their commentary on our review 2, where they highlight quality of unrecorded alcohol as a relevant dimension for alcohol-attributable burden of disease. Unrecorded alcohol includes some categories 3 which have been produced mainly in the same circumstances as recorded alcoholic beverages and then diverted or brought across jurisdictions legally. However, other unrecorded categories often are not controlled for quality in the same way as usual alcoholic beverages, either because they are produced at home or illegally or because they are not intended for human consumption (such as medicinal tinctures 4). In many high-income countries, these non-standardized products probably account for less than half of the unrecorded alcohol (e.g. 5, 6), but in low- and middle-income countries the proportion is usually much higher. An estimated 25% of the global alcohol consumption is estimated as unrecorded 7, and this proportion is highest in low- and middle-income countries 8. Estimating the contribution of unrecorded alcohol to the alcohol-attributable burden of disease correctly is thus crucial for comparative risk assessments 9, 10. The arguments of Lachenmeier & Walch 1 raise two questions: (1) should we estimate attributable burden for all or part of unrecorded alcohol with different relative risk functions than for recorded alcohol and (2) are we confident about the inclusion of all the deaths from substances such as methanol under alcohol-attributable deaths? To answer the first question, at the moment, based on prior reviews 3, 11, the same relative risk functions are used for unrecorded consumption as for recorded consumption in the estimation of the burden of disease 2. This approach still seems justified, as no new evidence on differential relative risks is available and, to date, the few studies that have found higher risks 12 could potentially be explained by heavy or very heavy drinking occasions, due in part to the lower price of unrecorded alcohol. We believe that the burden lies with those claiming higher risks for unrecorded consumption to provide empirical evidence in support of this assertion. The second question raised 1 is more complicated to answer. Overall, the contribution of alcohol poisoning is underestimated globally for four reasons: first, many estimates are restricted to ethanol and do not include substances such as methanol (i.e. methanol poisoning; see 1); secondly, there is frequent miscoding of alcohol poisoning deaths as cardiovascular deaths, albeit not to the degree that could explain the detrimental impact of alcohol on cardiovascular disease 13, 14; thirdly, incidence and prevalence of all fully alcohol-attributable causes of death are underestimated because of stigma 15; and finally, there is underestimation because alcohol as a contributory cause to illicit drug overdose deaths is usually not reflected on death certificates (e.g. 16). In this sense, Lachenmeier & Walch 1 should be taken as a plea to improve future statistics on alcohol poisonings to include unrecorded consumption. Finally, we agree strongly 1 that additional research on unrecorded consumption in relation to burden of disease is needed. This research needs to recognize that ‘unrecorded alcohol’ includes subcategories with varying likelihoods of contamination, and that contaminants may vary with customary methods of brewing or distilling the alcohol. Based on toxicological knowledge and past research 3, most of these contaminants will not impact upon risk for disease above alcohol, but some may, varying considerably across cultures and by geography (e.g. 17, 18). Thus, it would probably be a long time before the results are robust enough to be used in global burden of disease estimates, even if new research is initiated. None.
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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 | 0,001 | 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 | 0,001 | 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.
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