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Enregistrement W1647136229 · doi:10.1111/j.1360-0443.2006.01572.x

MEASURING ALCOHOL CONSUMPTION—IS A REASONABLE CHANGE ALWAYS REASONABLE? RESPONSE TO KIEFER & SPANAGEL (2006)

2006· article· en· W1647136229 sur OpenAlexaff
Gerhard Gmel, Kathryn Graham, Hervé Kuendig, Sandra Kuntsche

Notice bibliographique

RevueAddiction · 2006
Typearticle
Langueen
DomaineMedicine
ThématiqueNutritional Studies and Diet
Établissements canadiensCentre for Addiction and Mental HealthWestern University
Organismes subventionnairesnon disponible
Mots-clésBody weightMedicineAlcohol intakePopulationAlcoholAlcohol consumptionAffect (linguistics)Weight lossConsumption (sociology)Body mass indexDemographyPsychologyGerontologyEnvironmental healthObesity

Résumé

récupéré en direct d'OpenAlex

We would like to thank Kiefer & Spanagel [1] for their thought-provoking letter related to improving alcohol measurement. Their point is provoking, because to our knowledge no cross-cultural research, including meta-analyses to measure relative-risks (e.g. estimates of mortality and morbidity such as those presented in the Report of the World Health Organization [2]), has applied adjustments for body weight. Even the Global Burden of Disease Study [3] did not use weight-adjusted cut-offs to define the three levels of alcohol intake, although they did use different cut-offs for men and women. It would be interesting to see whether the findings from this report would have been different if adjustments for body weight had been used. We fully agree with Kiefer & Spanagel [1] that adjustment for body weight or the use of a standard measure of ethanol intake as g/kg/day (gram pure ethanol per kg body weight per day) has the potential to avoid some alcohol measurement inequalities due to sex and ethnically or culturally based population differences. This may be particularly true for clinical research, as mentioned by Kiefer & Spanagel [1], where body weight can be measured objectively in the clinical setting. However, for cross-cultural survey research there are a number of considerations that could make the routine adjustment for body weight problematic. First, as noted previously regarding adjusting alcohol consumption measures for biological gender differences [4], adjusting for the drinker size of the person would be inappropriate if alcohol consumption differences that affect peak blood alcohol consumption (e.g. drinking pace and whether alcohol is consumed with meals) are correlated with the person’s size. For example, if smaller people tend to drink more slowly compared with larger people, their peak blood alcohol level might be the same or even lower than that of larger people who drank the same quantity but more quickly, even though the overall dose per body weight for the smaller person would be higher than for the larger person. In this scenario, adjusting for body weight would be inappropriate for estimating negative consequences related to the acute effects of alcohol. This is not to say that adjusting for body weight is not a good idea if all other things are equal. However, in cross-cultural comparisons all other things are rarely equal, and such an adjustment could produce erroneous results if body size and drinking pattern or style are confounded. On the other hand, as the world grows increasingly small and we engage increasingly in cross-national studies, it is good advice to take into consideration the impact of cultural differences in body size as well as other cultural differences that apply to how we measure and interpret alcohol consumption when making comparisons across various countries. It is possible that the extent of high-risk drinking is underestimated in some countries where smaller body weight and riskier drinking patterns coincide, as noted above. A second factor that affects interpretation of overall volume of alcohol consumption is drinking pattern—that is, the harmful effects of drinking 14 drinks per week are likely to depend on how the drinks were consumed (e.g. 14 on one day versus two drinks per day with a meal). Thus, drinking pattern is likely to be a much more important factor than adjusting for body weight, particularly for the acute effects of alcohol such as driving under the influence, and again drinking patterns are known to vary across cultures [3]. In addition, survey measures of alcohol consumption are far from perfect, and there are a number of other alcohol measurement biases that may affect differentially different countries for which the effects of adjusting for body weight would either be inappropriate or irrelevant. For example, survey instruments on alcohol consumption have been found to underestimate sales data by between 30 and 70%[5, 6]. Unfortunately, these factors are not constant in cross-country comparisons and thus influence comparisons. Given the magnitude of such a bias, body weight adjustments would be a minor factor for the increase in the validity of measurement instruments. Survey measures of body weight may also have systematic errors that would put into question routine adjustments for body weight. In particular, there is evidence in the literature that self-reports of body weight are often biased, and this bias does not necessarily apply equally to the population, with women and those who are overweight more likely to under-report weight and differential biases associated with different age groups [7, 8]. Finally, our study showed differences in estimates of mean consumption within a country of as much as 30%, depending on the type of alcohol measure used (e.g. generic versus beverage specific measurement, graduated frequency versus quantity–frequency). Furthermore, the type of measure producing the highest estimate was not consistent across countries. For this type of comparative research, the bias of not adjusting for body weight would be irrelevant, as we compared different instruments within a country and compared these differences between instruments across countries. For between-instrument comparisons within countries, body weight adjustment would be a constant factor applying to all instruments in the same way, and thus would not bias the between-instrument comparisons. To conclude, we think that Kiefer & Spanagel have raised an important issue. Specifically, however, there is a need to develop measures of alcohol consumption that are valid for cross-cultural comparisons before adjustment for drinker size can be applied.

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 candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,364
Score d'incertitude au seuil1,000

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)0,0010,001

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 Opus0,084
Tête enseignante GPT0,287
Écart entre enseignants0,203 · 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.

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

Citations0
Publié2006
Routes d'admission1
Résumé présentoui

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