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ObjectivesTo better understand the outcome benefits of community health services for the aged (CHSA) and provide bottom-up identity for development, this study examined the impact of using CHSA on well-being of older adults from both objective and subjective dimensions.MethodsData from 1,411 people aged 60+ in Shaanxi, China was used in this study. The OLS estimate was used to analyze the impact of using CHSA on well-being of older adults. Then, the instrumental variable estimate was further hired to examine associations among variables to address the potential endogeneity concerns. The heterogeneity among disabled and non-disabled group was also estimated.ResultsFor objective well-being, the mental health (β = 0.44) and financial well-being (β = 0.59) of older people using CHSA were significantly higher than those not using any service. The impact on objective well-being were more significant in non-disabled group. For subjective well-being, life meaning (β = 0.54) and security (β = 0.72) were positively associated with CHSA utilization, while independence index (β = −0.33) was negatively related with CHSA utilization. The subjective well-being of disabled group using services increased more than non-disabled group.ConclusionFindings underscore the positive, albeit group-selective, role of CHSA in improving well-being of older people in China and imply the necessity of high-quality development of CHSA and the targeted differentiation strategy.

Thermal protection performance (TPP) is an important index to evaluate the performance of firefighting clothing. The purpose of this work is to build a model to predict the TPP values of fabrics with fewer variables. Two properties of flame-retardant cotton were tested with TPP values under different air gaps, and the correlations between these properties were also analyzed. A combined model was established by integrating multivariate nonlinear regression model and gradient boosting regression tree model. Then the combined model was compared with these two single models. The results showed that the correlation coefficients between gram weight and thickness of fabric and TPP value were 0.833 and 0.837, respectively, indicating a strong correlation. The correlation coefficient between air gap and TPP value was 0.304, indicating a weak correlation. In predicting the thermal protective performance of flame-retardant cotton, this study employed a multivariate nonlinear regression model, a Gradient Boosting Regression Tree (GBRT) model, and a combined model. After comparing various evaluation metrics, it was finally decided to adopt the combined model for predicting the thermal protective performance values of flame-retardant cotton. This method improved the prediction accuracy of thermal protective performance, facilitating the promotion and application of the combined model. Furthermore, when exploring the thermal protective performance of flame-retardant cotton, the use of fewer variables to establish the prediction model can not only significantly simplify the complex structure of the model but also greatly enhance the analysis efficiency, ensuring the efficiency and precision of the research process.