Network modeling of the relationship between intestinal symptoms and depression: A cross-sectional study using NHANES data
Year: 2025
Type: article
Abstract: OBJECTIVE: The "brain-gut axis" theory highlights the link between depression and gastrointestinal symptoms, garnering increasing attention. This research aims to apply a network analysis model to identify key symptoms and their relationships in both depression and gastrointestinal disorders. The goal is to aid nursing staff in implementing targeted interventions and personalized care. METHODS: Data were collected from the NHANES 2009-2010 cycle, involving 5196 participants. We assessed symptom scores and clinical information using the depression screening questionnaire (DPQ) and the bowel health questionnaire (BHQ). R package bootnet was used to create a regularized partial correlation network to explore the relationship between depression and gastrointestinal symptoms. To ensure stability and accuracy, we conducted Bootstrap analysis and applied a residual-based method to account for confounding factors in the symptom network. RESULT: The network analysis shows that "hopelessness" is the key node in the cluster of depressive symptoms, while among gastrointestinal symptoms, "constipation" demonstrated the highest centrality score, indicating its prominence within the symptom network. Additionally, "fatigue" is closely related to both "diarrhea" and "constipation," and "sleep problems" are notably linked to constipation. Overall, the network model exhibits strong stability. CONCLUSION: The study identified "fatigue" and "sleep problems" as key connections between depression and gastrointestinal symptoms. This finding suggests a potential avenue for clinical intervention: for patients experiencing diarrhea and constipation, enhancing sleep quality and reducing fatigue may help improve these intestinal issues. By addressing sleep and fatigue, we could potentially break the vicious cycle of psychosomatic symptoms that links depression with gastrointestinal problems.
Source: Applied Nursing Research
Authors: Qian Ye, Ying Liu
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,690
OpenAlex ID: W4416418858
