Latent class analysis of symptom clusters in preventive enterostomy with colorectal cancer patients based on nutritional status

Background There is a close relationship between nutritional status and symptom clusters. However, research on the characteristics of symptom clusters in different nutritional statuses is still limited. The purpose of this study was to explore the heterogeneity of symptom clusters in different patient categories by using latent class analysis and to provide direction and key guidance for clinical symptom cluster management in different patient populations. Methods This cross-sectional study used convenience sampling to recruit colorectal cancer patients with preventive enterostomy from three tertiary hospitals in Fujian Province. Data were collected using the following instruments: a general information questionnaire, the Chinese version of the Adult Pain Behavior Scale (APBS), the Hamilton Anxiety Scale (HAMA), the Hamilton Depression Scale (HAMD), the Athens Insomnia Scale (AIS), and the Cancer Appetite and Symptom Questionnaire (CASQ). After data collection, latent class analysis (LCA) was applied to explore heterogeneous subgroups of nutritional status-symptom clusters. Univariate and multivariate analyses were conducted to identify factors influencing subgroup classification. Results A total of 350 questionnaires were collected, which revealed four latent categories: the malnourished-high symptom cluster group, the suboptimal nutrition-higher symptom cluster group, the moderate nutrition-moderate symptom cluster group, and the well-nourished-low symptom cluster group. Multivariate logistic regression analysis showed that chronic diseases and tumor location were significant factors influencing the latent categories ( P  < 0.05). Conclusion The findings of this study indicated that the subgroups of disease symptoms under different nutritional statuses exhibited distinct characteristics. By identifying the subgroups of symptoms, it is helpful to provide reference and guidance for formulating more effective and accurate intervention and management strategies for patients with preventive enterostomy.