Exploring factors influencing the quality of life in diabetes: a network analysis-based study

Abstract

ObjectiveThe purpose of this study was to explore the key pathways leading to low quality of life in type 2 diabetes patients by means of network analysis, so as to provide the possibility of effective interventions.MethodsThe study involved 1,011 adult type 2 diabetes patients from a tertiary hospital in Harbin. Data was collected through questionnaires, and network analysis was performed using R software to assess the centrality and predictability of each node.Results“Depression” and “Submission” (weight = 0.26), “Depression” and “Physiological field” (weight = -0.16), exhibit the strongest associations. Overall, “Depression” has the highest weight in the association with diabetes symptom, regarding betweenness, “Depression” and “Submission” exhibit the highest scores, Furthermore, the analysis of closeness centrality reveals that “Depression” and “Submission” share the highest level of proximity, it suggests that they have the shortest distances to other network factors in our research network.ConclusionDepression and Submission are likely to be key factors affecting the quality of life of people with diabetes. Providing psychological support and scientific coping strategies for diabetes patients may be an effective way to help them live a better life.