Background As the phenomenon of ageing continues to intensify, home and community-based services (HCBSs) have been increasingly important in China. However, the association between HCBSs utilization and depressive symptoms in older adults in China is unclear. Consequently, this study aimed to examine the association between HCBSs utilization and depressive symptoms in Chinese older adults. Methods This study included 7,787 older adults (≥ 60 years old) who were recruited within the framework of the 2018 China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale (CES-D-10). HCBSs utilization was assessed via the question, “What kind of HCBSs were being utilized in their community?”. Data were analyzed using binary logistic regression models and generalized hierarchical linear models (GHLM). Results Of the 7,787 participants, 20.0% (n = 1,556) reported that they utilized HCBSs, and 36.7% (n = 2,859) were evaluated that they had depressive symptoms. After adjusting for individual- and province-level covariates, the HCBSs utilization was found to be associated with depressive symptoms (OR = 1.180, 95% CI: 1.035–1.346, p < 0.05). Additionally, the depressive symptoms were significantly associated with gender, residence, educational level, marital status, number of chronic diseases, self-rated health (SRH), smoking, and provincial Gross Domestic Product (GDP) per capita. Conclusions This study found HCBSs utilization might be a protective factor against depressive symptoms in Chinese older adults. It is of utmost significance for the government to provide targeted HCBSs at the community level to address the unmet care needs of older adults, which can reduce the occurrence of negative emotions, consequently contributing to less severe depressive symptoms.

Background As the phenomenon of ageing continues to intensify, home and community-based services (HCBSs) have become of increasing importance in China. However, few studies have assessed the impact of HCBSs utilization on depressive symptoms among older adults. This study aimed to examine the association between HCBSs utilization and depressive symptoms in Chinese older adults. Methods This study included 7,787 older adults (≥ 60years old) who were recruited within the framework of the 2018 China Health and Retirement Longitudinal Study (CHARLS). Depressive symptoms were assessed using the 10-item Center for Epidemiological Studies Depression Scale (CES-D-10). HCBSs utilization was assessed via the question, “What kind of HCBSs were being utilized in their community?”. Data were analyzed using generalized hierarchical linear models. Results Of the 7,787 participants, 20.1% (n = 1,567) reported they utilized HCBSs, and 36.7% (n = 2,859) were currently with depressive symptoms. After adjusting for individual- and province-level covariates, the HCBSs utilization was found to be associated with depressive symptoms (OR = 1.189, 95% CI:1.043–1.356, p < 0.01) among older adults. Additionally, the depressive symptoms were associated with gender, residence, educational level, marital status, number of chronic diseases, self-rated health, smoking, and provincial GDP per captia. Conclusions This study found HCBSs utilization might be a protective factor against depressive symptoms in Chinese older adults. It is important that the government provides targeted HCBSs at the community level to address the unmet care needs of older adults to reduce the occurrence of negative emotions and consequently the depressive symptoms.

BackgroundHome and community-based services are considered an appropriate and crucial caring method for older adults in China. However, the research examining demand for medical services in HCBS through machine learning techniques and national representative data has not yet been carried out. This study aimed to address the absence of a complete and unified demand assessment system for home and community-based services.MethodsThis was a cross-sectional study conducted on 15,312 older adults based on the Chinese Longitudinal Healthy Longevity Survey 2018. Models predicting demand were constructed using five machine-learning methods: Logistic regression, Logistic regression with LASSO regularization, Support Vector Machine, Random Forest, and Extreme Gradient Boosting (XGboost), and based on Andersen's behavioral model of health services use. Methods utilized 60% of older adults to develop the model, 20% of the samples to examine the performance of models, and the remaining 20% of cases to evaluate the robustness of the models. To investigate demand for medical services in HCBS, individual characteristics such as predisposing, enabling, need, and behavior factors constituted four combinations to determine the best model.ResultsRandom Forest and XGboost models produced the best results, in which both models were over 80% at specificity and produced robust results in the validation set. Andersen's behavioral model allowed for combining odds ratio and estimating the contribution of each variable of Random Forest and XGboost models. The three most critical features that affected older adults required medical services in HCBS were self-rated health, exercise, and education.ConclusionAndersen's behavioral model combined with machine learning techniques successfully constructed a model with reasonable predictors to predict older adults who may have a higher demand for medical services in HCBS. Furthermore, the model captured their critical characteristics. This method predicting demands could be valuable for the community and managers in arranging limited primary medical resources to promote healthy aging.