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在高度不同环境中的相对停留时间对重度饮酒者分布的影响。

Impact of Relative Residence Times in Highly Distinct Environments on the Distribution of Heavy Drinkers.

作者信息

Mubayi Anuj, Greenwood Priscilla E, Castillo-Chávez Carlos, Gruenewald Paul, Gorman Dennis M

机构信息

Mathematical and Computational Modeling Sciences Center, Arizona State University, Tempe, AZ 85287, USA.

出版信息

Socioecon Plann Sci. 2010 Mar 1;44(1):45-56. doi: 10.1016/j.seps.2009.02.002.

Abstract

Alcohol consumption is a function of social dynamics, environmental contexts, individuals' preferences and family history. Empirical surveys have focused primarily on identification of risk factors for high-level drinking but have done little to clarify the underlying mechanisms at work. Also, there have been few attempts to apply nonlinear dynamics to the study of these mechanisms and processes at the population level. A simple framework where drinking is modeled as a socially contagious process in low- and high-risk connected environments is introduced. Individuals are classified as light, moderate (assumed mobile), and heavy drinkers. Moderate drinkers provide the link between both environments, that is, they are assumed to be the only individuals drinking in both settings. The focus here is on the effect of moderate drinkers, measured by the proportion of their time spent in "low-" versus "high-" risk drinking environments, on the distribution of drinkers.A simple model within our contact framework predicts that if the relative residence times of moderate drinkers is distributed randomly between low- and high-risk environments then the proportion of heavy drinkers is likely to be higher than expected. However, the full story even in a highly simplified setting is not so simple because "strong" local social mixing tends to increase high-risk drinking on its own. High levels of social interaction between light and moderate drinkers in low-risk environments can diminish the importance of the distribution of relative drinking times on the prevalence of heavy drinking.

摘要

饮酒是社会动态、环境背景、个人偏好和家族史的一种函数。实证调查主要集中在识别高饮酒水平的风险因素上,但在阐明其潜在作用机制方面做得很少。此外,几乎没有尝试将非线性动力学应用于在人群层面研究这些机制和过程。本文介绍了一个简单的框架,其中将饮酒建模为在低风险和高风险关联环境中的一种社会传染过程。个体被分为轻度、中度(假定可流动)和重度饮酒者。中度饮酒者是两种环境之间的纽带,也就是说,他们被假定为唯一在两种环境中都饮酒的个体。这里关注的是中度饮酒者在“低”风险与“高”风险饮酒环境中所花费时间的比例对饮酒者分布的影响。我们接触框架内的一个简单模型预测,如果中度饮酒者在低风险和高风险环境之间的相对停留时间是随机分布的,那么重度饮酒者的比例可能会高于预期。然而,即使在高度简化的情况下,实际情况也并非如此简单,因为“强烈的”局部社会混合往往会自行增加高风险饮酒。低风险环境中轻度和中度饮酒者之间高水平的社会互动会削弱相对饮酒时间分布对重度饮酒流行率的重要性。

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