Network characteristics of comorbid symptoms in alcohol use disorder
Background Individuals with alcohol use disorder (AUD) often experience symptoms such as anxiety, depression, and decreased sleep quality. Although these are not diagnostic criteria, they may increase dependence risk and complicate treatment. This study aims to analyze comorbidities and their comple...
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| Format: | Article |
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Taylor & Francis Group
2025-12-01
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| Series: | Annals of Medicine |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/07853890.2024.2446691 |
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| author | Xin Yu Wen Zhang Can Wang Guolin Mi Xiuzhe Chen Yanhu Wang Xu Chen |
| author_facet | Xin Yu Wen Zhang Can Wang Guolin Mi Xiuzhe Chen Yanhu Wang Xu Chen |
| author_sort | Xin Yu |
| collection | DOAJ |
| description | Background Individuals with alcohol use disorder (AUD) often experience symptoms such as anxiety, depression, and decreased sleep quality. Although these are not diagnostic criteria, they may increase dependence risk and complicate treatment. This study aims to analyze comorbidities and their complex relationships in AUD patients through epidemiological surveys and network analysis.Materials and methods Using multi-stage stratified cluster random sampling, we selected 27,913 individuals and identified those with AUD for the study. All screened subjects were assessed with the General Health Questionnaire, Pittsburgh Sleep Quality Index, and Simple Coping Style Questionnaire, and diagnosed according to DSM-IV criteria. Network analysis and visualization were performed in R 4.4.0. The qgraph and bootnet packages in R were used to obtain partial correlation network analysis and node centrality of mental health, sleep quality, and coping styles in individuals with AUD through the estimateNetwork function. The bootnet package was used to assess the accuracy and stability of the network. The bnlearn package in R was used to construct directed acyclic graph (DAG) for individuals with AUD using the Bayesian hill-climbing algorithm.Results In the partial correlation network, among the three major comorbidity categories, ‘anxiety/depression’ was most strongly associated with ‘sleep quality’. ‘Anxiety/depression’ and ‘sleep quality’ had the highest node centrality, with ‘sleep latency’ also showing notable centrality. The DAG results indicated that ‘sleep latency’ had the highest probability priority, directly affecting ‘anxiety/depression’ and key sleep quality symptoms such as ‘subjective sleep quality’, ‘sleep disturbances’, ‘sleep duration’, and ‘sleep efficiency’, while also indirectly influencing other symptoms.Conclusions Among the comorbid symptoms of AUD, sleep latency appears to be a key factor in triggering other comorbid symptoms. This study provides a basis for interventions aimed at reducing the comorbid symptoms of AUD and promoting recovery. |
| format | Article |
| id | doaj-art-a043d52bfde845e0b97b4bb001e88f4d |
| institution | Kabale University |
| issn | 0785-3890 1365-2060 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Annals of Medicine |
| spelling | doaj-art-a043d52bfde845e0b97b4bb001e88f4d2025-01-13T08:22:34ZengTaylor & Francis GroupAnnals of Medicine0785-38901365-20602025-12-0157110.1080/07853890.2024.2446691Network characteristics of comorbid symptoms in alcohol use disorderXin Yu0Wen Zhang1Can Wang2Guolin Mi3Xiuzhe Chen4Yanhu Wang5Xu Chen6School of Special Education and Rehabilitation, BinZhou Medical University, Yantai, ChinaDepartment of Psychiatry, Binzhou People’s Hospital, Shandong First Medical University, Binzhou, ChinaDepartment of Psychiatry, Shandong Mental Health Center, Shandong University, Jinan, ChinaDepartment of Psychiatry, Shandong Mental Health Center, Shandong University, Jinan, ChinaDepartment of Psychiatry, Shandong Mental Health Center, Shandong University, Jinan, ChinaDepartment of Psychiatry, Shandong Mental Health Center, Shandong University, Jinan, ChinaSchool of Special Education and Rehabilitation, BinZhou Medical University, Yantai, ChinaBackground Individuals with alcohol use disorder (AUD) often experience symptoms such as anxiety, depression, and decreased sleep quality. Although these are not diagnostic criteria, they may increase dependence risk and complicate treatment. This study aims to analyze comorbidities and their complex relationships in AUD patients through epidemiological surveys and network analysis.Materials and methods Using multi-stage stratified cluster random sampling, we selected 27,913 individuals and identified those with AUD for the study. All screened subjects were assessed with the General Health Questionnaire, Pittsburgh Sleep Quality Index, and Simple Coping Style Questionnaire, and diagnosed according to DSM-IV criteria. Network analysis and visualization were performed in R 4.4.0. The qgraph and bootnet packages in R were used to obtain partial correlation network analysis and node centrality of mental health, sleep quality, and coping styles in individuals with AUD through the estimateNetwork function. The bootnet package was used to assess the accuracy and stability of the network. The bnlearn package in R was used to construct directed acyclic graph (DAG) for individuals with AUD using the Bayesian hill-climbing algorithm.Results In the partial correlation network, among the three major comorbidity categories, ‘anxiety/depression’ was most strongly associated with ‘sleep quality’. ‘Anxiety/depression’ and ‘sleep quality’ had the highest node centrality, with ‘sleep latency’ also showing notable centrality. The DAG results indicated that ‘sleep latency’ had the highest probability priority, directly affecting ‘anxiety/depression’ and key sleep quality symptoms such as ‘subjective sleep quality’, ‘sleep disturbances’, ‘sleep duration’, and ‘sleep efficiency’, while also indirectly influencing other symptoms.Conclusions Among the comorbid symptoms of AUD, sleep latency appears to be a key factor in triggering other comorbid symptoms. This study provides a basis for interventions aimed at reducing the comorbid symptoms of AUD and promoting recovery.https://www.tandfonline.com/doi/10.1080/07853890.2024.2446691Alcohol use disordersleep qualitymental healthcoping stylesepidemiological surveysnetwork analysis method |
| spellingShingle | Xin Yu Wen Zhang Can Wang Guolin Mi Xiuzhe Chen Yanhu Wang Xu Chen Network characteristics of comorbid symptoms in alcohol use disorder Annals of Medicine Alcohol use disorder sleep quality mental health coping styles epidemiological surveys network analysis method |
| title | Network characteristics of comorbid symptoms in alcohol use disorder |
| title_full | Network characteristics of comorbid symptoms in alcohol use disorder |
| title_fullStr | Network characteristics of comorbid symptoms in alcohol use disorder |
| title_full_unstemmed | Network characteristics of comorbid symptoms in alcohol use disorder |
| title_short | Network characteristics of comorbid symptoms in alcohol use disorder |
| title_sort | network characteristics of comorbid symptoms in alcohol use disorder |
| topic | Alcohol use disorder sleep quality mental health coping styles epidemiological surveys network analysis method |
| url | https://www.tandfonline.com/doi/10.1080/07853890.2024.2446691 |
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