Zhongguo quanke yixue (Sep 2022)
Trajectories and Influencing Factors of Somatic Symptom Clusters in Frail Elderly People in Nursing Homes: a Longitudinal Study
Abstract
Background The somatic symptom clusters may be associated with increased risk of adverse outcomes in frail elderly people. Relevant studies in China have mainly adopted a cross-sectional design with neglect of the trajectory of somatic symptom clusters in this group. Objective To explore the characteristics of somatic symptom clusters at different time points and influencing factors in elderly people with frailty in nursing homes in Chengdu. Methods From November 2019 to January 2020, 206 frail elderly people were selected from 6 nursing homes in Chengdu by convenience sampling, and surveyed using the general data questionnaire and Memory Symptom Assessment Scale (MSAS) for 3 times〔at baseline (T0) , 6 (T1) , and 12 months later (T2) 〕. Exploratory factor analysis was carried out for symptoms with an incidence of ≥20% at different time points. Latent growth mixture model (LGMM) was used to identify the change trajectory of somatic symptom clusters across the above-mentioned three time points. Logistic regression analysis was used to identify the potential factors associated with the trajectory category. Results By exploratory factor analysis, 5 factors were extracted at each of the three time points. Neurological symptom cluster, energy deficiency symptom cluster, respiratory symptom cluster and digestive symptom cluster all appeared at the three time points. In addition, senescence-related symptom cluster also occurred at T0 and T1, and other symptom cluster occurred at T2. The MSAS score of each symptom cluster differed significantly across three time points (P<0.05) . Four heterogeneous trajectories of frailty symptom clusters were obtained by LGMM model fitting, which were named as "high decline" "low rise" "medium maintenance" and "high rise", accounting for 16.5%, 12.5%, 66.0% and 5.0%, respectively. Multivariate Logistic regression analysis showed that the number of chronic diseases was independently associated with the "high decline" or "high rise" trajectory, and the number of medications was independently associated with the "high rise" trajectory (P<0.05) . Conclusion There are various trajectories of somatic symptom clusters in frail elderly people in nursing homes, and each of the trajectories has a different independently associated factor. To provide more appropriate services for this population, medical workers in nursing homes can dynamically adjust nursing services according to the trajectories and associated factors of somatic symptom clusters.
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