OBJECTIVE This study examined how social associations from a person's social network may be associated with their own alcohol consumption. METHOD Alcohol consumption behavior was examined among the social networks of 784 survey respondents (54% female, Mage = 35.3 years), using egocentric social network analysis. Participants (egos) were recruited via a panel aggregator and completed an online survey about the frequency of their alcohol consumption and that of the 20 most influential people in their lives (alters). The survey also explored who these alters were (family, friends, work colleagues) and the interrelationships among these alters. RESULTS Egos who consumed alcohol, or consumed alcohol more frequently, were surrounded by more alters who also drank alcohol and felt closer (had stronger ties) to these alters. These relationships remained statistically significant when controlling for demographic and other variables. The social networks of those who consumed alcohol more frequently were more densely intertwined. CONCLUSIONS Alcohol may serve to initiate social connections and be a "social glue" that reinforces relationships. These strong social associations present a potential barrier to individuals who wish to reduce their alcohol consumption because they have few close social connections who do not drink alcohol (or who do so infrequently), and their highly interconnected social networks make it difficult to socialize only with those who do not drink frequently. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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澳大利亚社区样本中的社会关联和饮酒：以自我为中心的社交网络分析。

目的 这项研究探讨了一个人的社交网络中的社会关联如何与他们自己的饮酒量相关。方法 使用以自我为中心的社交网络分析，对 784 名调查受访者（54% 女性，Mage = 35.3 岁）的社交网络中的酒精消费行为进行了调查。参与者（自我）是通过小组聚合器招募的，并完成了一项关于其饮酒频率以及生活中 20 位最有影响力的人（改变者）饮酒频率的在线调查。该调查还探讨了这些改变者是谁（家人、朋友、同事）以及这些改变者之间的相互关系。结果 饮酒或更频繁饮酒的自我会被更多也饮酒的分身包围，并且感觉与这些分身更接近（有更强的联系）。当控制人口统计和其他变量时，这些关系在统计上仍然显着。饮酒频率较高的人的社交网络更加紧密地交织在一起。结论 酒精可能有助于建立社交联系，并成为加强人际关系的“社交粘合剂”。这些强大的社会联系对那些希望减少饮酒的个人构成了潜在的障碍，因为不喝酒（或不经常喝酒）的人几乎没有密切的社会联系，而且他们高度互联的社交网络使得他们很难只与喝酒的人进行社交活动。不经常喝酒的人。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。