Xu Shuqi, Zhao Ranran, Wang Jincheng, Yang Xue, Wang Lan, An Cuixia, Wang Xueyi, Wang Ran
Department of Psychiatry, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China.
Mental Health Center, Hebei Medical University, Shijiazhuang, Hebei, China.
Front Endocrinol (Lausanne). 2025 Jul 30;16:1553691. doi: 10.3389/fendo.2025.1553691. eCollection 2025.
Harmful drinking habits can have a profound effect on individual health. However, there is currently a lack of network analysis studies on clinical indicators related to drinking population. The aim of this study was to investigate the relationships among drinking characteristics, cognitive functions, liver and kidney functions, and glucose and lipid levels in alcohol drinkers through the application of network analysis.
We conducted a stratified random sampling survey of 1,432 male employees in Gaocheng District, Hebei Province, in 2016. The Alcohol Dependence Scale (ADS) and the Alcohol Use Disorders Identification Test (AUDIT) were utilized to evaluate alcohol-related behaviors. Cognitive functions were assessed via the Hopkins Verbal Learning Test (HVLT), the Brief Visuospatial Memory Test (BVMT), Digit Symbol Coding Test (DSCT), and Digit Span Test (DST). Additionally, biochemical indicators such as blood glucose and lipid levels and hepatic and renal functions were measured. Analyses were performed to identify central symptoms and bridge symptoms of this network.
In our network analysis, the nodes representing TC, AST, AST/ALT, and ALT had the highest strength centrality. TC and AST presented the highest expected influence centrality. The closeness centrality indices for all the indicators performed well. The node DSCT ranked highly in terms of betweenness centrality.
Correlations may exist among cognitive function, glycemic and lipid profiles, and hepatic-renal function in individuals with varying alcohol consumption patterns. Lipid and liver function indicators were identified as the most central factors in the network model. In the clinic, practitioners may focus on these abnormal central indicators as potential intervention targets to enhance the quality of life in alcohol drinkers.
有害饮酒习惯会对个人健康产生深远影响。然而，目前缺乏关于饮酒人群临床指标的网络分析研究。本研究的目的是通过应用网络分析来调查饮酒者的饮酒特征、认知功能、肝肾功能以及血糖和血脂水平之间的关系。
2016年，我们对河北省藁城区的1432名男性员工进行了分层随机抽样调查。使用酒精依赖量表（ADS）和酒精使用障碍识别测试（AUDIT）来评估与酒精相关行为。通过霍普金斯言语学习测试（HVLT）、简短视觉空间记忆测试（BVMT）、数字符号编码测试（DSCT）和数字广度测试（DST）评估认知功能。此外，还测量了血糖、血脂水平以及肝肾功能等生化指标。进行分析以确定该网络的中心症状和桥梁症状。
在我们的网络分析中，代表总胆固醇（TC）、谷草转氨酶（AST）、AST/ALT比值和谷丙转氨酶（ALT）的节点具有最高的强度中心性。TC和AST呈现出最高的预期影响中心性。所有指标的接近中心性指数表现良好。节点DSCT在中介中心性方面排名很高。
不同饮酒模式个体的认知功能、血糖和血脂状况以及肝肾功能之间可能存在相关性。脂质和肝功能指标被确定为网络模型中最核心的因素。在临床上，从业者可将这些异常的核心指标作为潜在干预靶点，以提高饮酒者的生活质量。
