WHO/ISBRA Study on State and Trait Markers of Alcohol Use and Dependence: Analysis of Demographic, Behavioral, Physiologic, and Drinking Variables That Contribute to Dependence and Seeking Treatment
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Résumé
Background Discussions between the World Health Organization (WHO) and the International Society on Biomedical Research on Alcoholism (ISBRA) identified the need for a multiple‐center international study on state and trait markers of alcohol abuse and alcohol dependence. The reasoning behind the generation of such a project included the need to understand the alcohol use characteristics of diverse populations and the performance of biological markers of alcohol use in a variety of settings throughout the world. A second major reason for initiating this study was to collect DNA for well‐structured and stratified association studies between genetic markers and/or “candidate” genes and behavioral/physiological phenotypes of importance to predisposition to alcohol dependence. Methods An extensive interview instrument was developed with leadership from the U.S. National Institute on Alcohol Abuse and Alcoholism (NIAAA). The instrument was translated from English to Finnish, French, German, Japanese, and Portuguese (Brazilian). One thousand eight hundred sixty‐three subjects were recruited at five clinical centers (Montreal, Canada; Helsinki, Finland; Sapporo, Japan; São Paulo, Brazil; and Sydney, Australia). The subjects responded to the structured interview and provided blood and urine samples for biochemical analysis. This article focuses on the demographic characteristics of the study subjects, their drinking habits, alcohol‐dependence characteristics, comorbid psychiatric and other drug variables, and predictors for seeking treatment for alcohol dependence. Multiple logistic regression models were constructed and used to explore variables that contribute to various levels of alcohol consumption, to a diagnosis of alcohol dependence, and to seeking treatment for alcohol dependence. ANOVA with post hoc comparisons, χ 2 , and Pearson moment calculations were used as necessary to assess additional relationships between variables. Results A number of factors previously noted in disparate studies were confirmed in our analysis. Men consumed more alcohol than women, Asians consumed less alcohol than whites or Blacks, alcohol‐dependent subjects consumed more alcohol than nondependent subjects, alcohol consumption increased with age, and an increased level of education (university or postgraduate education) reduced the percentage of such individuals in the category designated as heavy drinkers (>210 g alcohol/week) and in the group who were currently in treatment for dependence. However, our analysis allowed for much more detailed comparisons; for example, although men drank more than women on a g/day basis, the differences were less pronounced on g/kg/day basis, and alcohol‐dependent women drank equal amounts of alcohol as alcohol‐dependent men on a g/kg/day basis. Antisocial personality characteristics or reports of trouble sleeping when an individual stops drinking were associated with higher alcohol intake. The most important of the tested factors that contributed to a DSM‐IV diagnosis of dependence, however, was the report of anxiety if an individual stopped drinking. In terms of the various criteria within the DSM‐IV criteria for alcohol dependence, no one criterion seemed to be prominent for individuals who sought alcohol dependence treatment, but the higher the number of criteria met by the individual, the higher was the probability that he or she would be in treatment. Conclusions This initial report is the beginning of the “data mining” of this rich data set. The cross‐national/cross‐cultural aspects of this study allowed for multiple comparisons of variables across several ethnic/racial groups and allowed for assessment of biochemical markers for alcohol intake and predisposition to alcohol dependence in diverse settings.
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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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 découle