The use of the Internet has a promoting effect on the physical health of the older people. However, previous studies are mostly focused on the perspective of the overall population, or limited to the direct effects, ignoring the exploration of the mechanism of action and the perspective of the older people. Based on the data of the China Family Panel Survey (CFPS) in 2014, 2016, 2018, and 2020, this study found that the use of the Internet has a significant effect on the physical health of the older people, especially among the population groups of females, rural residents, and those living in central and western regions of China. In addition, this study also found that the use of the Internet by the older people can increase their exercise frequency, thereby improving their physical health. Therefore, to promote active aging, this study proposes to further increase the popularity of the Internet among the older people, encourage the introduction of age-appropriate Internet systems and sports facilities, create an online fitness platform for the older people, and promote scientific fitness programs for them.
The existing research on residents’ health care consumption mostly covers medical care consumption and seldom regards residents’ health care consumption as an independent research object. This article takes residents' healthcare consumption as the research object and aims to explore the impact of socioeconomic status on healthcare consumption and its mechanisms. The data of this study came from the 2018-China Family Panel Studies (CFPS). The binary probit regression model and the Tobit model explored the impact mechanism of residents’ income, education, occupation, and physical activity on health care consumption decision-making and health care expenditure, respectively. The research results showed that, from the perspective of the direct influence mechanism, residents’ work income (0.029, p < 0.01) and education level (811.149, p < 0.01) had a significant positive impact on health care consumption. Residents whose occupations (−99.697, p < 0.01) tend to be more skilled and also have higher health care consumption. From the perspective of the mediating mechanism, residents' physical exercise duration had a significant positive impact on their participation in healthcare consumption (0.005, p < 0.01) but had a weaker impact on healthcare consumption expenditure (21.678, p < 0.1). In general, socioeconomic status represented by income, education, and occupation had a significant positive impact on residents’ health care consumption. The duration of physical exercise also played an important mediating role.
In this paper, a comprehensive quantitative and biological neural network optimization model of sports industry structure is thoroughly studied and analyzed using knowledge graphs. To address the problems of poor performance interpretability deficiency of knowledge graph-based recommendation methods in the face of relational sparse graphs, a pretraining-based implicit characterization algorithm strategy is proposed for the recall stage, which can solve the problems of difficulty in going online and high delay in the recall stage of the recommendation system while improving the accuracy, and not only this can be applied in the recall stage, but also the sorting and postsorting modules can be used as features. To study the relationship between signaling activity and energy metabolism of pyramidal neurons, an empirical model of the synaptic vesicle cycle is proposed to simulate the synaptic transmission process, the role played by energy metabolism in synaptic transmission is studied from the perspective of feedback control, and the quantitative relationship between neuronal pulse discharge frequency, energy consumption, and information quantity in dendritic integration is analyzed using the cable theory and atrial chamber model. It was found that, when 0 ≤ ε ≤ 0.6 , the chaotic region shrinks and eventually disappears with the increase of the memory factor ε ; however, when 0.6 ≤ ε ≤ 1 is used, chaos is recreated and the chaotic area gradually increases with the increase of the memory factor ε . This paper conducts comparative experiments on data sets in the recommendation domain and verifies that the proposed model and the feature intersection module can effectively perform feature interaction between items and entities, thus enhancing the recommendation effect.
Using data from China Family Panel Studies (CFPS) and based on the Probit and Tobit models, this study investigates the impact of air pollution on residents’ outdoor exercise behaviour from the microscopic level. Specifically, this study examined the effects of PM2.5 index changes on residents’ decision to participate in outdoor exercise and the duration of outdoor exercise participation. The empirical results show that the increase of PM2.5 index has a significant inhibitory effect on residents’ participation in outdoor exercise, and has passed the robustness test and endogeneity test. Further testing found that the inhibitory effect was significantly different between urban and rural areas, and in the central, north-eastern and western regions where economic development was relatively backward, the conclusion that air pollution inhibited residents’ outdoor exercise behaviour still holds true. However, the level of air pollution had no significant effect on the outdoor exercise behaviour of residents in the eastern region. So, while air pollution discourages residents from participating in outdoor exercise, the results are more applicable to less economically developed areas.
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