Abstract
BACKGROUND: 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. METHOD: 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. RESULTS: 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. CONCLUSION: 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.