Research on the Impact of Mutual Elderly Care on the Physical and Mental Health of Rural Elderly--An Empirical Study Based on the Propensity Score Matching Method (PSM)

Research on the Impact of Mutual Elderly Care on the Physical and Mental Health of Rural Elderly--An Empirical Study Based on the Propensity Score Matching Method (PSM) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Research on the Impact of Mutual Elderly Care on the Physical and Mental Health of Rural Elderly--An Empirical Study Based on the Propensity Score Matching Method (PSM) Jialiang LIU, xiaohan LIU, Guangyao LIU, Bin HU This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4898207/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract To study the impact of mutual care on the physical and mental health of rural elderly, and provide countermeasures and suggestions for the long-term development of mutual care. METHODS: Data from the 2018 China Health and Aged Care Tracking Survey (CHARLS) were selected from 8,369 elderly people aged ≥60 years old, and propensity score matching (PSM) was carried out using STATA (MP17) software using nearest-neighbor matching, kernel matching, and radius matching, and then heterogeneity was used to analyze the mean effect values among different populations. RESULTS: The results of propensity score matching PSM showed that participation in mutual care had a significant positive effect on the mental health of the rural elderly, with a net effect of 0.020~0.027, and a significant negative effect on the physical health of the rural elderly, with a net effect of -0.029~-0.030. Heterogeneity analyses showed that participation in mutual care had no significant effect on the physical and mental health of the rural elderly who did not suffer from chronic diseases. Physical and mental health does not have a significant effect. The net effect is -0.06031 to -0.035, and the net effect is 0.029 to 0.030. Conclusion: the rate of rural elderly people's participation in mutual aid is low, and participation in mutual aid has different degrees of influence on the physical and mental health of rural elderly people, and different characteristics of rural elderly people's participation in mutual aid have different degrees of influence on their physical and mental health. Mutual aid for the elderly Rural elderly Physical health Mental health Propensity score matching Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction By the end of 2022, the national elderly population aged 60 years and above was 28,040,000 people, accounting for 19.8% of the total population, and the national elderly population aged 65 years and above was 209,780,000 people, accounting for 14.9% of the total population, with the proportion of the elderly aged 60 years old in rural areas being 23.81%, and that of the elderly aged 65 years old and above being 17.72% [ 1 ][ 2 ] . It can be seen that the number of elderly people in China is growing rapidly, the degree of aging is deepening, and rural areas are characterized by "aging before getting rich" and "aging before getting ready" [ 3 ] . In order to cope with the aging of the population, the World Health Organization (WHO) promulgated the active aging strategy [ 4 ] . Among them, mutual aid for the elderly is a full embodiment of the concept of active aging. It initially aims to promote active aging [ 5 ] . In the theoretical framework of active aging, physical and mental health is highly related to active aging and is a prerequisite for active aging [ 6 ] . Currently, there are numerous scholars who provide a comparable methodology in the research on the theme of mutual aid for the elderly and the theme of physical and mental health of the rural elderly. However, there are fewer studies on the relationship between the two, and clarifying the impact of mutual aid on the physical and mental health of rural elderly can enable us to correctly recognize the current status of mutual aid implementation and help the state make timely adjustments to the problems that exist in the process of mutual aid. Based on the above background, this paper will explore the impact of mutual aid on the physical and mental health of rural elderly, analyze the problems that exist in China's implementation of mutual aid strategies, and provide references for reforms related to active aging. Compared with the existing results, the contribution of this paper has two main points: first, the impact effect of mutual aid on physical and mental health (physical health and mental health dimensions) is measured, which provides an empirical basis for the scientific formulation of active aging policy. Second, the propensity score matching method (PSM) is used to scientifically assess the effects of physical and mental health of rural elderly people, which solves the endogeneity problem of previous assessment models and improves the effectiveness of policy assessment. Literature review In promoting the process of active aging, the physical and mental health of rural elderly has been a hot research topic for scholars at home and abroad. Studies on the physical and mental health of rural older adults have mainly focused on the following aspects. The first is about the conceptual definition and measurement of physical and mental health of rural older adults. Physical and mental health includes two aspects: physical health and mental health. The World Health Organization defines mental health as a state of well-being that enables one to realize one's own abilities, cope with the stresses of normal life and be able to work productively and contribute to one's community, and does not consider mental illness alone. Sun Jianping [ 7 ] believes that mental health refers to the state of adaptation and integrity that an individual's mind can achieve within the scope of its own and environmental conditions, that is, it refers to the development of the individual's state of mind into an optimal state within the scope of the physical, intellectual, and emotional well-being of others without contradiction. Existing studies on mental health have used different scales to measure it from different perspectives, and more Chinese studies have used negative mental health scales or customized positive mental health measures [ 46 ] . Physiological health refers to the functioning of organs and systems of the body in a good state of operation, which requires that the physiological functions of various tissues, organs and systems of the body can be coordinated with each other and are in a normal state [ 8 ][ 9 ] . With the transformation of the disease spectrum and the development of geriatric health assessment, people's understanding of the assessment of physiological health of the elderly has been deepening, and Luo Huijiang [ 10 ] believes that physiological health is reflected by the ability of physical activity. reflected by physical activity capacity. According to Zhou Yeqin, physiological health mainly refers to an individual's ability to maintain the relative homeostasis of his or her physiological system while experiencing environmental changes [ 11 ] . Secondly, the causal analysis of the physical and mental health of the rural elderly. The first is about the analysis of the causal factors of the mental health of the elderly, and most researchers analyze the impact on the mental health of the elderly from the perspectives of the mode of residence, family intergenerational relations, and health status [ 12 ] [ 13 ] [ 14 ] [ 15 ] . There are also scholars who analyze the impact of mental health of the elderly from the levels of social capital, leisure mode, and community services. By using multi-indicator factor structural equation modeling, Yang Yinan [ 16 ] and others concluded that the use of community mental comfort services has an irreplaceable positive effect on the mental health of the elderly. Wen Shaozheng [ 17 ] et al. by using the Chinese CHARLS database and PSM-DID methodology concluded that: community home care services improve the mental health of disabled older adults, the effect of community home care services on the mental health of disabled older adults is heterogeneous, and the health services have a significant effect on the improvement of the mental health of disabled older adults. Hu Rong et al [ 18 ] , based on CGSS 2012 data, logistic Steele regression analysis showed that social trust, socialization frequency, and recreation and leisure factors in social capital variables had a significant impact on the mental health of the elderly. Sammi R Chekroud [ 19 ] study found that physical activity contributes to mental health, but not the more exercise the better. Secondly, in the analysis of factors affecting the physical health of the elderly, some scholars have analyzed from the perspective of social participation, and concluded that social participation can reduce help to alleviate the deterioration of the health of the elderly, can reduce the risk of chronic diseases, and has a positive and significant impact on all types of health [ 20 ] [ 21 ] . However, with the development of the digital era and the advancement of the Internet application of age-appropriate transformation, the impact of online social participation of the elderly on their health has become the focus of scholars' attention, and some scholars have found that online social participation increases the loneliness of the elderly, and excessive online social participation has a negative impact on the physical health of the elderly [ 22 ] . In addition, in terms of social support, some scholars have found that pension level has a significant positive relationship on the health status of the elderly [ 23 ] . Among Chinese aged 45 years and above, older age, difficulties in daily living and not working were high risk factors for physical activity levels [ 24 ] . The above studies present different perspectives on the physical and mental health of the elderly, which provide important insights for us to understand the influencing factors of the physical and mental health of the elderly. Based on this, this paper advocates further exploring the physical and mental health of the rural elderly from the perspective of mutual care, which is of great theoretical value and practical significance for the revitalization of the countryside and the realization of active aging. Research Objects and Methods 1.1 Research Objectives The China Health and Retirement Longitudinal Study (CHARLS) aims to collect a set of high-quality microdata representing Chinese households and individuals aged 45 years and older, which can be used to analyze the problem of population aging in China, and to promote interdisciplinary research on aging CHARLS The national baseline survey was conducted in 2011, covering 150 county-level units, 450 village-level units, and 17,000 people in about 10,000 households Data from CHARLS 2018 were used to select elderly people whose residence type was rural and who were ≥ 60 years of age or older, and 8,369 study participants were finally included after removing missing values and retaining important key variables. 1.2 Selection of variables Mutual-help social pension is no longer simply the construction of hardware facilities or mutual help among the elderly, but the continuous validity and reconfiguration of informal social resources in rural areas, making full use of all kinds of human resources in rural areas (especially the elderly) of the idle time, resources, the development of a variety of forms of financial mutual aid, mutual aid, mutual aid, mutual aid, cultural mutual aid mode of social pensions Nina Liu [ 5 ] . Therefore, the corresponding question in the questionnaire is "Have you carried out the following social activities in the past month?". In the questionnaire, the corresponding question is "Did you do any of the following social activities in the past month?", of which five options are "Visiting the door, socializing with friends", "Playing mahjong, chess, cards, going to the community room", "Offering help to relatives, friends or neighbors who do not live with you", "Participating in the cultural mutual support model of the elderly". ", "Participate in volunteer activities", and "Take care of a sick or disabled person who is not with you". The value of 1 is assigned to any of the five mutual aid behaviors, and 0 is assigned to any of the five behaviors. The explanatory variable of this paper is the degree of mental health of the elderly. Depression status of middle-aged and older adults was measured using a simplified 10-entry version of the Center for Epidemiological Survey, Depression Scale (CES-D) by the Center for Epidemiological Studies. The scale had 8 negatively oriented questions and 2 positively oriented questions. All 10 questions of the scale were scored on a 4-point scale (rarely or not at all = 0, not too much = 1, sometimes or half the time = 2, most of the time = 3), and the two positive mood questions were reverse scored, and then the scores of the 10 questions were summed to construct a composite index of depressed mood in older adults, which was scored in the range of 0 to 30 points. A score of 10 or less was defined as no depressed mood, and a score of 10 or more as depressed mood, with higher scores indicating more severe depression and lower mental health in older adults [ 26 ] . Self-care was measured with the Somatic Life Self-Care Scale, developed by Lawton and Brody in 1969 to assess an individual's ability to perform daily activities. The scale includes 6 entries for dressing, bathing, eating, getting in/out of bed, toileting, and controlling urination and defecation, and the above questions were measured on a 4-point scale, assigning a score of 0 for I can take care of myself completely, a score of 1 for I have some difficulty but can do it on my own, a score of 2 for I need help, and a score of 3 for I can't take care of myself at all, and then the total of scores of the 6 questions was added up, and the score of 0 was defined as a healthy elderly person, and the score of greater than 0 as a dysfunctional Older people. The specific assignment of each variable is shown in Table 1 Table 1 Assignment of values to each variable Variable Name Assignment case Mutual Aid Behavior No = 0; Yes = 1 Gender Male = 0; Female = 1 Political Profile Mass = 0; Party member = 1 Religion No = 0; Yes = 1 Age 60–69 years old = 1; 70–79 years old = 2; 80 years old and above = 3 Chronic Disease None = 0; Yes = 1 Marital status Married with spouse = 1;Unmarried divorced = 2; Widowed = 3 Medical Insurance No = 1; Urban workers' medical insurance (health insurance) = 2; Cooperative medical care, urban and rural residents' medical care, urban residents' medical care = 3; Commercial medical insurance = 4; Other medical insurance = 5 Pension Insurance No = 1; Pension for government agencies or civil servants = 2; Pension for career employees = 3; Basic pension insurance for employees = 4 Depression No = 0; Yes = 1 Activity status No = 0; Yes = 1 Alcohol use No = 0; Yes = 1 1.3 Research Methods This paper uses StataMP17 software for statistics and analysis, and the propensity score matching method (PSM) to study the effect of mutual care on the physical and mental health of rural elderly. The test level α = 0.05. Results 2.1 Descriptive statistical analysis By calculating the minimum, maximum, mean and standard deviation statistics of each variable, the average value of mutual aid behavior of the survey respondents is 0.335, and the specific values of each variable are shown in Table 2 . Table 2 Maximum, minimum, mean and standard deviation of each variable Variables Maximum value Minimum value Mean value Standard deviation Mutual Aid Behavior 0 1 0.355 0.479 Gender 0 1 0.512 0.500 Alcohol consumption 0 1 0.300 0.459 Political profile 0 1 0.085 0.278 Religion 0 1 0.112 0.315 Age 1 3 1.550 0.712 Chronic Disease 0 1 0.673 0.470 Marital status 1 3 1.428 0.809 Medical Insurance 1 5 2.959 0.550 Pension Insurance 1 4 1.194 0.710 Depression 0 1 0.366 0.482 Mobility deficits 0 1 0.276 0.447 2.2 Common support test In order to ensure the matching quality of the sample data, so that the treatment and control groups can be matched to more similar individuals while reducing the loss of matched samples, the range of the common support domain needs to be as wide as possible. The kernel density function was further plotted after the derivation of the propensity score to assess the common support domain after matching. See Figs. 1 and 2.Before matching, the kernel density functions of the treatment and control groups showed more significant differences. After matching, most of the observed values were in the common range of values and the two overlapped significantly. Therefore, it can be assumed that the matching effect is ideal and the common support assumption is satisfied. 2.3 Balance test The balance after matching is tested. After the kernel matching method, the standard errors of the control variables before and after matching5 and the specifics of error abatement are shown in Table 3 , Fig. 3 , and Fig. 4 . Table 3 shows that before matching, the differences in gender, age, marital status, and whether or not they drank alcohol were statistically significant (P < 0.05). After matching, the differences between the two groups of older adults in terms of gender, age, marital status, and whether or not they drank alcohol were not statistically significant (P < 0.05). The standardized mean errors of the matched variables were all less than 10%, and the results of the t-test (P < 0.05) showed that none of the differences between groups of the covariates were significant after matching, indicating that the samples were well matched. It can be seen that the matching significantly reduces the sample bias and enhances the similarity of the characteristics of the two groups of samples, indicating that the two groups of samples after matching are well-balanced. Table 3 Error reduction before and after matching for each variable Variable Sample average value Standard deviation (%) Deviation reduction (%) T -test treatment group control group T -value p >| t | Age Before Matching 1.527 1.564 -5.1 -2.23 0.026 After Matching 1.528 1.527 0.1 97.8 0.04 0.965 Chronic disease status Pre-Match 0.673 0.672 0.1 0.05 0.961 After Match 0.673 0.676 -0.7 -539.2 -0.28 0.782 Marital status Pre-Match 1.465 1.408 7.0 3.07 0.002 Match After 1.464 1.435 3.6 48.7 1.36 0.174 Medical insurance Match Before 2.973 2.951 4.1 1.80 0.073 Match After 2.972 2.970 0.5 89.0 0.18 0.859 Pension insurance Match Before 1.204 1.190 2.0 0.87 0.386 Match After 1.203 1.192 1.6 21.1 0.60 0.550 Alcohol consumption Match Before 0.324 0.286 8.4 3.68 0.001 Match After 0.324 0.311 2.8 66.2 1.08 0.281 Gender Match Before 0.531 0.501 6.0 2.64 0.008 Match After 0.531 0.535 -0.9 84.6 -0.36 0.719 Religion Match Before 0.112 0.112 -0.0 -0.01 0.995 Match After 0.112 0.111 0.2 -1238.6 0.07 0.943 Political profile Match Before 0.078 0.088 -3.5 -1.50 0.132 Match After 0.078 0.077 0.5 84.1 0.22 0.827 2.4 Effect of mutual support on mental health and physical health status of elderly people In order to test the robustness of Propensity Score Matching (PSM) results in this study, three different methods i.e., Near Neighbor Matching, Radius Matching and Kernel Matching were used to estimate the effect. And the average treatment effect ATT of the treatment group was used to indicate the effect of the impact, as shown in Table 4 and Table 5 .After the propensity score matching PSM analysis, all three matching methods have a significant impact on the mental health and physical health of rural Chinese older adults. For the mental health of rural older adults, participation in mutual care significantly negatively affects their ability to perform activities of daily living with a net effect of 0.020 to 0.027. For the physical health of rural older adults, the PSM results show that participation in mutual care significantly negatively affects the ability to perform activities of daily living of older adults, with a net effect of -0.029 to − 0.03. Table 4 Mental Health of Rural Older Adults ATT Variables Method Treat Controls ATT S.D t -Value Mutual retirement behavior Neighborhood Matching 0.386 0.366 0.020 0.012 1.72* Radius Matching 0.386 0.358 0.028 0.012 2.53** Kernel Matching 0.385 0.358 0.027 0.011 2.47** Table 5 Ability to perform activities of daily living for the elderly in rural areas ATT Variables Method Treat Controls ATT S.D t -Value Mutual retirement behavior Neighborhood Matching 0.255 0.283 -0.029 0.011 -2.73*** Radius Matching 0.255 0.285 -0.031 0.010 -3.02*** Kernel Matching 0.255 0.285 -0.030 0.010 -2.96*** 2.5 Heterogeneity test Health status can largely affect older people's participation in mutual aid for the elderly. Therefore, exploring the heterogeneity of impacts across different types of older people can enrich the existing literature on the impact of mutual care on the physical and mental health of rural older people. Here, the samples were grouped and processed to assess the between-group differences in the impact of chronic disease conditions, using the presence or absence of chronic disease as a marker. Heterogeneity tests show that for older people who do not suffer from chronic diseases, the impact of mutual aging on their mental health and physical health is not significant under any of the three matching methods. In contrast, for rural older adults with chronic diseases, mutual care has a significant effect on their mental health and physical health under all three matching methods. The maximum net effect of mutual aid in old age on the mental health of rural elderly with chronic diseases is 0.03, and the maximum net effect of the effect on physical health is -0.035. See Tables 6 , 7 , 8 , and 9 . Table 6 Mental Health of Rural Older Adults without Chronic Disease Variables Method Treat Controls ATT S.D t -V alue Mutual retirement behavior Neighborhood Matching 0.360 0.339 0.021 0.020 1.04 Radius Matching 0.356 0.338 -0.031 0.022 1.13 Kernel Matching 0.360 0.337 -0.023 0.019 1.19 Table 7 Physical Health of Rural Older Adults without Chronic Disease Variables Method Treat Controls ATT S.D t -V alue Mutual retirement behavior Neighborhood Matching 0.203 0.228 -0.024 0.017 -1.41 Radius Matching 0.203 0.223 -0.020 0.016 -1.19 Kernel Matching Method 0.203 0.226 -0.022 0.016 -1.136 Table 8 Mental health of rural elderly with chronic diseases Variables Method Treat Controls ATT S.D t -V alue Mutual retirement behavior Neighborhood Matching 0.399 0.367 0.029 0.014 2.04** Radius Matching 0.399 0.368 0.030 0.014 2.24** Kernel Matching 0.399 0.369 0.030 0.014 2.20* Table 9 Physical health of rural elderly with chronic diseases Variables Method Treat Controls ATT S.D t -V alue Mutual retirement behavior Neighborhood Matching 0.280 0.310 -0.031 0.014 -2.31** Radius Matching 0.280 0.314 -0.035 0.013 -2.72*** Kernel Matching 0.280 0.313 -0.034 0.013 -2.67*** Discussion 3.1 Low participation rate of rural elderly in mutual aid in old age behavior The results of the study show that the participation of rural elderly in mutual aid in old age behavior is low, only 30%. This result is the same as the findings of Liu Zhuo [ 27 ] and Wang Ruibin [ 28 ] . This may be due to the fact that the rural elderly are influenced by the deep-rooted traditional culture of raising children to prevent old age, and believe that participation in mutual aid is the children's inability to old age to themselves, which not only causes the elderly to lose face, but also causes the children to be labeled as unfilial, which leads to the fact that, even if the elderly have the desire to participate in the idea of mutual aid in old age, they are forced to refuse to participate in mutual aid due to the secular world, so that the elderly are not willing to give more attention to the way of old age other than the children's family old age. As a result, they are reluctant to learn more about other forms of old-age care besides their children's family care, which ultimately leads to a lack of awareness of the mutual care model among the elderly. On the other hand, rural elderly in China generally have a low level of education and are susceptible to the influence of traditional family concepts, and therefore spend most of their time on household chores and taking care of grandchildren in their old age, which leads to the lack of conditions for rural elderly to participate in higher-level social activities and a low awareness of participation [ 6 ] . The sustained and healthy operation of the mutual aid elderly care model cannot be separated from the participation of the government, village committees, village sages, volunteers and other more social levels. However, as one of the most important roles at the grassroots level, "village two committees" have a limited role in organizing and guiding the elderly to participate in mutual care. "As a bridge between the government and the countryside, village committees are one of the main organizers of rural mutual care. However, due to the impact of rural reforms and social changes, villages have been hollowed out seriously [ 29 ] , and it is difficult for village-level organizations to play their due organizational functions and guiding roles in rural mutual care for the elderly. In addition, policies and regulations related to mutual care for the elderly have been introduced late and are not well targeted, and many local grass-roots governments have not allocated appropriate funds for the development of the elderly due to a lack of awareness of their responsibilities, while the collective and community support for and investment in mutual care for the elderly are often influenced by the attitude of local governments. 3.2 Participation in mutual care significantly improves the physical health status of rural elderly people Whether analyzed from the perspective of the whole sample or from the perspective of the rural elderly with chronic diseases, participation in mutual care significantly improves the physiological health status of the rural elderly, a result consistent with the study of Wu Qiaoli [ 30 ] . Mutual care in essence focuses on the elderly, they are both service providers and service recipients Yi Zhiqi [ 31 ] , is the elderly in social activities to play their own strength to help each other, support each other [ 32 ] social behavior, rural elderly participation in mutual care to a certain extent, expanding the channels of their participation in social activities, the overall activity of the previously sedentary elderly has been increased!, whether it is simply getting out of the house or developing more regular physical activity habits. Additionally, increased activity can help to reduce adverse health effects such as smoking and increased body mass [ 33 ] , and can significantly prevent the onset of disability in older adults [ 34 ] . To a certain extent, the health care services provided by mutual care for the elderly can raise the level of health awareness among the elderly, help them to take the initiative and spontaneously change their lifestyles and habits, and develop a correct perception of recreation and health care, thereby reducing the level of risk of illness and minimizing the number of visits to the doctor. 3.3 Participation in mutual care significantly reduces the mental health of rural older people Analyzed from the perspective of the whole sample or from the perspective of rural older adults with chronic diseases, participation in mutual care significantly reduces the mental health status of rural older adults and increases the risk of depression among rural older adults. This finding breaks with the original preconceptions and is also inconsistent with some previous studies [ 35 ] . Possible explanations are that geography is a transmission of blood ties, and the social network of acquaintances in which traditional rural areas are situated provides a social foundation for rural mutual care [ 36 ] , and the social network is an informal institution that contains rich resources for old age [ 37 ] . Trusting relationships based on family ties play a key role in social networks [ 38 ] , however, some studies have indicated that family ties are the main reason for the high prevalence of depression in the elderly population [ 39 ] . Children in some families consider mutual support as a way of old age that makes them 'lose face' [ 40 ] ." Children are the most important part of the social support system of the rural left-behind elderly [ 41 ] , but with the accelerated rate of urbanization, the number of children working outside the home has increased, the number of rural left-behind elderly has increased [ 42 ] , and the children's investment in the elderly, such as emotional support and economic support, has decreased. At the same time, with the continuous development of modern science and technology, the rural elderly are constantly disconnected from society, resulting in a sense of inferiority, and the rural elderly are difficult to achieve independence in emotional comfort [ 42 ] . In addition, the elderly have a certain enthusiasm to participate in mutual care in the short term, but they do not have a strong sense of cooperation, and in the long-term practice, due to the lack of timeliness of mutual service feedback, fairness is difficult to effectively measure and other issues, they will still produce individual negative consciousness due to the reality of conflict of interest [ 43 ] . When living in mutual aid nursing homes, some of the elderly often have disputes due to different personalities, social experiences and values, causing psychological pressure on both sides, which is not conducive to the physical and mental health of the elderly [ 44 ] . Social phenomena such as aging, empty nesters, and separation of the young and the old are gradually aggravated. In order to reduce the social pressure of young people, the elderly will stay home to take care of their grandchildren, and even take out their own pensions and retirement pensions to help their children to ease the economic pressure. Under this double pressure, the elderly will be in an unhappy mood even if they participate in mutual help for the elderly. At the same time, the elderly who suffer from chronic diseases, because chronic diseases have the characteristics of prolonged illness, multiple organ complications, high rate of disability and death, the need for long-term treatment and care, and high treatment costs, especially those who suffer from a variety of chronic diseases at the same time, the disease itself and the pressure it brings in terms of economy, care, and spirit, etc. [ 45 ] which seriously affects the mental health status of the elderly. 3.4 Suggestions First: Improve laws and regulations, establish a long-term feedback mechanism, and create a favorable external environment for the implementation of mutual aid for the elderly. Carefully summarize the experiences of various regions in carrying out mutual aid for the elderly; strengthen the training of rural elderly service personnel through the opening of special professional courses, training programs, and free or subsidized training; and collaborate with a variety of educational and professional service organizations to achieve the sharing of resources and talents, and to alleviate the problem of human resource shortages in rural society. Strengthen collaboration with hospitals, schools, nursing homes and other organizations to carry out various forms of exchanges and training, to continuously improve the overall quality of the service team and enhance the quality of elderly services. At the same time, it can also actively collaborate with community and volunteer organizations to mobilize more social forces to provide support for the elderly. Second: Accelerating the cultivation of a new type of elderly care culture to promote diversification and sustainable development. With the help of the Internet and community publicity on mutual aid for the elderly, the elderly are gradually getting rid of their dependence on traditional ways of ageing; the culture of filial piety is publicized, and children are advocated to participate in mutual aid for the elderly as volunteers, so as to combine ageing at home with mutual aid for the elderly; the mutual aid method of combining "labour and support" is implemented, and the elderly in special hardship and the low-income elderly are encouraged to do some free, low-paid labour at the Happy Court. It also promotes the "labor-support" combination of mutual aid, encouraging the elderly in special hardship and the low-income elderly to do some free, low-paid labor in the Happiness Courts. On the other hand, the elderly, especially those who are able to take care of themselves, should abandon the notion that they are the ones being helped and realize that their skills, life experience and human resources can still produce social value; on this basis, a model of mutual assistance for the elderly in the rural community has been proposed in order to provide diversified, high-quality services for the elderly. Third: Paying attention to the mental health of the elderly When arranging for the elderly to live in a home, consider their personality, sleeping habits, and hobbies to meet their living and spiritual needs; encourage and advocate the participation of nursing, doctors, mental health counselors and other professionals in mutual care, improve the rural health care system, and improve the quality of mutual care services; increase the space for the elderly to improve their self-care activities; improve the quality of the elderly's care, and integrate medical care with mutual care. (c) Combining medical care with mutual support for the elderly, and emphasizing and preventing the possible effects of chronic diseases on the elderly. 4 Limitations and Future Research The data in this article uses only one year of cross-sectional data, which is a short observation period. Therefore, panel data for multiple years can be included in subsequent studies so that validation analyses can be conducted using more and more comprehensive indicators. Declarations Author Contribution Authors' contributions: Bin Hu proposed the research idea, designed the research propositions and controlled the quality of the final paper; Xiaohan Liu, Guangyao Liu, and Jialiang Liu completed the writing of the paper's data, the data organization, the statistical processing, and the graph drawing. Data Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request. References Qi Chen. Silver-haired economy calls for diversified supply [N]. Economic Herald,2024-01-08(001). Qi Ling. Empirical Analysis on the Demand and Influencing Factors of Rural Mutual Elderly Care in Northwest China under the Perspective of Aging[J]. China Health Care Management,2024,41(01):65-68+120. Chen Jian,Luo Qintao. 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Analysis of the current status of depression and its influencing factors in middle-aged and elderly chronic disease patients in China: an empirical analysis based on CHARLS data[J/OL]. Chinese Family Medicine:1-6[2024-07-06]. ZHANG Wenzhen,ZHANG Liangwen,FANG Ya. A study on the relationship between family intergenerational relationship patterns and depressive symptoms among the elderly in China[J]. Medicine and Society,2024,37(05):93-99. CHI Xiaohua, LU Jing, WANG Shuangyan, et al. Mental health status of the elderly in different aging modes[J]. Chinese Journal of Gerontology,2018,38(08):2013-2014. YANG Yinan,LI Sihua. The impact of community-based elderly mental comfort services on the mental health of the elderly - based on multi-indicator multi-factor structural equation modeling[J]. Journal of Sichuan University of Light and Chemical Engineering(Social Science Edition),2021,36(03):1-15. WEN Shaozheng,ZONG Zhanhong. Impact of community-based home care services on the mental health of disabled older adults[J]. Chinese Journal of Health Psychology,2023,31(11):1617-1623. HU Rong,HUANG Qianwen. Social capital, leisure mode and mental health of the elderly[J]. Hunan Social Science,2019(01):51-58. Chekroud S R , Ralitza G , Zheutlin A B ,et al. Association between physical exercise and mental health in 1-2 million individuals in the USA between 2011 and 2015: a cross-sectional study[J].Lancet Psychiatry, 2018:S221503661830227X-. Hu HH, Li YY, Zhang CH, et al. Social activity participation, health promotion and disability prevention-an empirical analysis based on the active aging framework[J]. China Population Science,2017(04):87-96+128. Cao Xiaoqing. Research on the impact of social participation on the health of empty nesters[J]. Intelligent Computer and Application,2020,10(03):362-366+370. Lv Mingyang,Peng Xizhe,Zhang Yi. The Internet and the health of rural elderly-micro evidence and impact mechanisms[J]. China Economic Issues, 2022(4):156-169. JIANG Shengzhong,GUO Xiuqi,YAN Shuhan,et al. Research on the impact of social pension insurance on the physical and mental health of the elderly[J]. Journal of Jiangxi University of Finance and Economics,2024(02):41-55. Li X , Zhang W , Zhang W ,et al. Level of physical activity among middle-aged and older Chinese people: evidence from the China health and retirement longitudinal study[J].BMC Public Health, 2020, 20(1). Nina Liu. Rural mutual social pension: Chinese characteristics and development path[J]. Journal of South China Agricultural University (Social Science Edition),2019, 18(01):121-131 XU Jinyan,ZHANG Qianqian. Impact of social participation on mental health among older adults--findings based on the CHARLS follow-up survey[J]. China Population Science,2023,37(04):98-113. LIU Zhuo,DU Wenjun. A study on service design to enhance the well-being of rural mutual care under the perspective of strengths[C]//Shenzhen University of Technology.2023 Proceedings of the Cross-Strait, Hong Kong and Macao Innovation Design Youth Academic Forum. [Publisher unknown],2023:9. Wang Ruibin. Research on the operation and optimization of the "time bank" mutual aid elderly care model in Zunyi City [D]. Guizhou University,2022. Wang Sibin. Comprehensive rural revitalization and the development of rural collectivity[J]. Journal of Peking University (Philosophy and Social Science Edition),2021,58(04):5-17. Wu Qiaoli. Research on the impact of mutual care on the health of rural left-behind elderly [D]. Zhongnan University of Economics and Law,2018. Yi Zhiqi,Sui Yujie,Sun Jinming. Gender Differences in Mutual Elderly Care Willingness, Form Preference and Service Content Preference[J]. Social Construction,2023,10(06):125-138. FAN Yixi,ZHAO Li,ZENG Haojie,et al. Research progress of mutual care for the elderly in the context of active aging[J]. Journal of Nursing,2023,38(21):122-125. Burgess G .What is the Potential for Community Currencies to Deliver Positive Public Health Outcomes? Case Study of Time Credits in Wisbech. Cambridgeshire, UK[J].other, 2017, 21(2). Hu, H., Li, Y. Y., Zhang, C., et al. Social Activity Participation, Health Promotion and Disability Prevention-An Empirical Analysis Based on the Active Aging Framework[J]. China Population Science,2017(04):87-96+128. Wu Qiaoli. Research on the impact of mutual care on the health of rural left-behind elderly [D]. Zhongnan University of Economics and Law,2018. Lv Haoran,Bao Tianxiao. Rural mutual care for the elderly: generation logic, development dilemma and optimization path[J]. Border Economy and Culture,2023(12):10-14. Ding Yuhao. Analysis of factors influencing social network on psychological depression of the elderly--an empirical study based on CGSS2017[J]. Operation and Management,2023(11):126-134. Guan Yuan,Huang Jianxin. The influence of social capital on the choice of e-commerce entrepreneurial behavior of farmers under the e-commerce environment--an empirical analysis based on the data of rural residents in CFPS2020[J]. Agriculture and Technology,2024,44(05):143-147. Li Miaoyan. Practical Exploration of Group Work Intervention for Community Integration of Elderly Migrants[D]. Guangzhou University,2020. Zhao Hohua. Difficulties in the Development of Rural Mutual Elderly Care under the Perspective of Embeddedness Theory and Cracking the Dilemma[J]. Contemporary Economic Research,2024(02):94-104. Xiao Jianying,Qing Qiurong. Research on the current situation and countermeasures of psychological care for rural left-behind elderly[J]. Northern Light,2019(09):66-67. Tan Lilong. Research on the path of rural self-supporting development in the context of active aging[J]. South China Journal,2023,(03):47-48+59. WANG Lijian,ZHU Yixin. From "Individual" to "Society": The Realistic Response of Rural Mutual Elderly Service[J]. Administrative Reform,2023(04):20-28. HE Jia,LIU Fang'e. Progress of research on mental health status of the elderly in different aging modes[J]. General Practice Nursing,2020,18(10):1186-1188. YAN Hong,LIU Shuwen. Current situation and influencing factors of mental health of chronically ill older adults[J]. Chinese Journal of Gerontology,2019,39(21):5366-5369. HAN Huiran,XU Lingyi,YANG Chengfeng. Impacts of multi-scale built environment on mental health of the elderly - empirical evidence from Hefei based on extreme gradient enhancement model[J]. Geography Research,2024,43(06):1502-1521.) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 17 Jan, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 09 Oct, 2024 Reviews received at journal 07 Oct, 2024 Reviews received at journal 22 Sep, 2024 Reviewers agreed at journal 10 Sep, 2024 Reviewers agreed at journal 08 Sep, 2024 Reviewers invited by journal 08 Sep, 2024 Editor assigned by journal 27 Aug, 2024 Editor invited by journal 22 Aug, 2024 Submission checks completed at journal 21 Aug, 2024 First submitted to journal 12 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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matching\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4898207/v1/b87338239509e082cfca289a.png"},{"id":64824503,"identity":"194b890e-6e77-4c5a-abf3-38cacc518fc2","added_by":"auto","created_at":"2024-09-19 08:24:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":17749,"visible":true,"origin":"","legend":"\u003cp\u003eAfter kernel density matching\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4898207/v1/5d6352f18dbb04f85a13b9d6.png"},{"id":64825131,"identity":"95e16dd4-02d9-4385-8422-97e7ec16d643","added_by":"auto","created_at":"2024-09-19 08:32:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":74342,"visible":true,"origin":"","legend":"\u003cp\u003eBalance test\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4898207/v1/8b6b8d9a2792da0fb3dfe09f.png"},{"id":64824500,"identity":"f7c90043-9382-4fa5-b23f-8f0c224b06fb","added_by":"auto","created_at":"2024-09-19 08:24:27","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32271,"visible":true,"origin":"","legend":"\u003cp\u003eBalance test\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4898207/v1/def99b728ebaad978f5f58bb.png"},{"id":74284695,"identity":"ab255f3f-9697-4847-b484-66628946c615","added_by":"auto","created_at":"2025-01-20 16:11:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1263231,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4898207/v1/0eb347e5-8523-4487-8c55-1d91b6c122e7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on the Impact of Mutual Elderly Care on the Physical and Mental Health of Rural Elderly--An Empirical Study Based on the Propensity Score Matching Method (PSM)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBy the end of 2022, the national elderly population aged 60 years and above was 28,040,000 people, accounting for 19.8% of the total population, and the national elderly population aged 65 years and above was 209,780,000 people, accounting for 14.9% of the total population, with the proportion of the elderly aged 60 years old in rural areas being 23.81%, and that of the elderly aged 65 years old and above being 17.72% \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. It can be seen that the number of elderly people in China is growing rapidly, the degree of aging is deepening, and rural areas are characterized by \"aging before getting rich\" and \"aging before getting ready\" \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. In order to cope with the aging of the population, the World Health Organization (WHO) promulgated the active aging strategy \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Among them, mutual aid for the elderly is a full embodiment of the concept of active aging. It initially aims to promote active aging \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. In the theoretical framework of active aging, physical and mental health is highly related to active aging and is a prerequisite for active aging \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Currently, there are numerous scholars who provide a comparable methodology in the research on the theme of mutual aid for the elderly and the theme of physical and mental health of the rural elderly. However, there are fewer studies on the relationship between the two, and clarifying the impact of mutual aid on the physical and mental health of rural elderly can enable us to correctly recognize the current status of mutual aid implementation and help the state make timely adjustments to the problems that exist in the process of mutual aid. Based on the above background, this paper will explore the impact of mutual aid on the physical and mental health of rural elderly, analyze the problems that exist in China's implementation of mutual aid strategies, and provide references for reforms related to active aging.\u003c/p\u003e \u003cp\u003eCompared with the existing results, the contribution of this paper has two main points: first, the impact effect of mutual aid on physical and mental health (physical health and mental health dimensions) is measured, which provides an empirical basis for the scientific formulation of active aging policy. Second, the propensity score matching method (PSM) is used to scientifically assess the effects of physical and mental health of rural elderly people, which solves the endogeneity problem of previous assessment models and improves the effectiveness of policy assessment.\u003c/p\u003e"},{"header":"Literature review","content":"\u003cp\u003eIn promoting the process of active aging, the physical and mental health of rural elderly has been a hot research topic for scholars at home and abroad. Studies on the physical and mental health of rural older adults have mainly focused on the following aspects. The first is about the conceptual definition and measurement of physical and mental health of rural older adults. Physical and mental health includes two aspects: physical health and mental health. The World Health Organization defines mental health as a state of well-being that enables one to realize one's own abilities, cope with the stresses of normal life and be able to work productively and contribute to one's community, and does not consider mental illness alone. Sun Jianping\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e believes that mental health refers to the state of adaptation and integrity that an individual's mind can achieve within the scope of its own and environmental conditions, that is, it refers to the development of the individual's state of mind into an optimal state within the scope of the physical, intellectual, and emotional well-being of others without contradiction. Existing studies on mental health have used different scales to measure it from different perspectives, and more Chinese studies have used negative mental health scales or customized positive mental health measures \u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e. Physiological health refers to the functioning of organs and systems of the body in a good state of operation, which requires that the physiological functions of various tissues, organs and systems of the body can be coordinated with each other and are in a normal state \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. With the transformation of the disease spectrum and the development of geriatric health assessment, people's understanding of the assessment of physiological health of the elderly has been deepening, and Luo Huijiang\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e believes that physiological health is reflected by the ability of physical activity. reflected by physical activity capacity. According to Zhou Yeqin, physiological health mainly refers to an individual's ability to maintain the relative homeostasis of his or her physiological system while experiencing environmental changes \u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSecondly, the causal analysis of the physical and mental health of the rural elderly. The first is about the analysis of the causal factors of the mental health of the elderly, and most researchers analyze the impact on the mental health of the elderly from the perspectives of the mode of residence, family intergenerational relations, and health status \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. There are also scholars who analyze the impact of mental health of the elderly from the levels of social capital, leisure mode, and community services. By using multi-indicator factor structural equation modeling, Yang Yinan \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e and others concluded that the use of community mental comfort services has an irreplaceable positive effect on the mental health of the elderly. Wen Shaozheng\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e et al. by using the Chinese CHARLS database and PSM-DID methodology concluded that: community home care services improve the mental health of disabled older adults, the effect of community home care services on the mental health of disabled older adults is heterogeneous, and the health services have a significant effect on the improvement of the mental health of disabled older adults. Hu Rong et al \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, based on CGSS 2012 data, logistic Steele regression analysis showed that social trust, socialization frequency, and recreation and leisure factors in social capital variables had a significant impact on the mental health of the elderly. Sammi R Chekroud\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e study found that physical activity contributes to mental health, but not the more exercise the better. Secondly, in the analysis of factors affecting the physical health of the elderly, some scholars have analyzed from the perspective of social participation, and concluded that social participation can reduce help to alleviate the deterioration of the health of the elderly, can reduce the risk of chronic diseases, and has a positive and significant impact on all types of health \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. However, with the development of the digital era and the advancement of the Internet application of age-appropriate transformation, the impact of online social participation of the elderly on their health has become the focus of scholars' attention, and some scholars have found that online social participation increases the loneliness of the elderly, and excessive online social participation has a negative impact on the physical health of the elderly\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. In addition, in terms of social support, some scholars have found that pension level has a significant positive relationship on the health status of the elderly \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Among Chinese aged 45 years and above, older age, difficulties in daily living and not working were high risk factors for physical activity levels \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe above studies present different perspectives on the physical and mental health of the elderly, which provide important insights for us to understand the influencing factors of the physical and mental health of the elderly. Based on this, this paper advocates further exploring the physical and mental health of the rural elderly from the perspective of mutual care, which is of great theoretical value and practical significance for the revitalization of the countryside and the realization of active aging.\u003c/p\u003e\n\n \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e\n\n"},{"header":"Research Objects and Methods","content":"\u003ch2\u003e1.1 Research Objectives\u003c/h2\u003e\u003cp\u003eThe China Health and Retirement Longitudinal Study (CHARLS) aims to collect a set of high-quality microdata representing Chinese households and individuals aged 45 years and older, which can be used to analyze the problem of population aging in China, and to promote interdisciplinary research on aging CHARLS The national baseline survey was conducted in 2011, covering 150 county-level units, 450 village-level units, and 17,000 people in about 10,000 households Data from CHARLS 2018 were used to select elderly people whose residence type was rural and who were ≥ 60 years of age or older, and 8,369 study participants were finally included after removing missing values and retaining important key variables.\u003c/p\u003e\u003ch2\u003e1.2 Selection of variables\u003c/h2\u003e\u003cp\u003eMutual-help social pension is no longer simply the construction of hardware facilities or mutual help among the elderly, but the continuous validity and reconfiguration of informal social resources in rural areas, making full use of all kinds of human resources in rural areas (especially the elderly) of the idle time, resources, the development of a variety of forms of financial mutual aid, mutual aid, mutual aid, mutual aid, cultural mutual aid mode of social pensions Nina Liu \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Therefore, the corresponding question in the questionnaire is \"Have you carried out the following social activities in the past month?\". In the questionnaire, the corresponding question is \"Did you do any of the following social activities in the past month?\", of which five options are \"Visiting the door, socializing with friends\", \"Playing mahjong, chess, cards, going to the community room\", \"Offering help to relatives, friends or neighbors who do not live with you\", \"Participating in the cultural mutual support model of the elderly\". \", \"Participate in volunteer activities\", and \"Take care of a sick or disabled person who is not with you\". The value of 1 is assigned to any of the five mutual aid behaviors, and 0 is assigned to any of the five behaviors.\u003c/p\u003e\u003cp\u003eThe explanatory variable of this paper is the degree of mental health of the elderly. Depression status of middle-aged and older adults was measured using a simplified 10-entry version of the Center for Epidemiological Survey, Depression Scale (CES-D) by the Center for Epidemiological Studies. The scale had 8 negatively oriented questions and 2 positively oriented questions. All 10 questions of the scale were scored on a 4-point scale (rarely or not at all = 0, not too much = 1, sometimes or half the time = 2, most of the time = 3), and the two positive mood questions were reverse scored, and then the scores of the 10 questions were summed to construct a composite index of depressed mood in older adults, which was scored in the range of 0 to 30 points. A score of 10 or less was defined as no depressed mood, and a score of 10 or more as depressed mood, with higher scores indicating more severe depression and lower mental health in older adults \u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. Self-care was measured with the Somatic Life Self-Care Scale, developed by Lawton and Brody in 1969 to assess an individual's ability to perform daily activities. The scale includes 6 entries for dressing, bathing, eating, getting in/out of bed, toileting, and controlling urination and defecation, and the above questions were measured on a 4-point scale, assigning a score of 0 for I can take care of myself completely, a score of 1 for I have some difficulty but can do it on my own, a score of 2 for I need help, and a score of 3 for I can't take care of myself at all, and then the total of scores of the 6 questions was added up, and the score of 0 was defined as a healthy elderly person, and the score of greater than 0 as a dysfunctional Older people. The specific assignment of each variable is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssignment of values to each variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable Name\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssignment case\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual Aid Behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 0; Yes = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale = 0; Female = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolitical Profile\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMass = 0; Party member = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 0; Yes = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60–69 years old = 1; 70–79 years old = 2; 80 years old and above = 3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Disease\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNone = 0; Yes = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried with spouse = 1;Unmarried divorced = 2; Widowed = 3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Insurance\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 1; Urban workers' medical insurance (health insurance) = 2; Cooperative medical care, urban and rural residents' medical care, urban residents' medical care = 3; Commercial medical insurance = 4; Other medical insurance = 5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension Insurance\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 1; Pension for government agencies or civil servants = 2; Pension for career employees = 3; Basic pension insurance for employees = 4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 0; Yes = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 0; Yes = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol use\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo = 0; Yes = 1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003ch3\u003e1.3 Research Methods\u003c/h3\u003e\u003cp\u003eThis paper uses StataMP17 software for statistics and analysis, and the propensity score matching method (PSM) to study the effect of mutual care on the physical and mental health of rural elderly. The test level α = 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Descriptive statistical analysis\u003c/h2\u003e \u003cp\u003eBy calculating the minimum, maximum, mean and standard deviation statistics of each variable, the average value of mutual aid behavior of the survey respondents is 0.335, and the specific values of each variable are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMaximum, minimum, mean and standard deviation of each variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaximum value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMinimum value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean value\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual Aid Behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol consumption\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.300\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePolitical profile\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.278\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.550\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.712\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic Disease\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.470\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.428\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.809\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical Insurance\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.959\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePension Insurance\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.194\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.482\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMobility deficits\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.447\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Common support test\u003c/h2\u003e \u003cp\u003eIn order to ensure the matching quality of the sample data, so that the treatment and control groups can be matched to more similar individuals while reducing the loss of matched samples, the range of the common support domain needs to be as wide as possible. The kernel density function was further plotted after the derivation of the propensity score to assess the common support domain after matching. See Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and 2.Before matching, the kernel density functions of the treatment and control groups showed more significant differences. After matching, most of the observed values were in the common range of values and the two overlapped significantly. Therefore, it can be assumed that the matching effect is ideal and the common support assumption is satisfied.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.3 Balance test\u003c/h2\u003e \u003cp\u003eThe balance after matching is tested. After the kernel matching method, the standard errors of the control variables before and after matching5 and the specifics of error abatement are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows that before matching, the differences in gender, age, marital status, and whether or not they drank alcohol were statistically significant (P \u0026lt; 0.05). After matching, the differences between the two groups of older adults in terms of gender, age, marital status, and whether or not they drank alcohol were not statistically significant (P \u0026lt; 0.05). The standardized mean errors of the matched variables were all less than 10%, and the results of the t-test (P \u0026lt; 0.05) showed that none of the differences between groups of the covariates were significant after matching, indicating that the samples were well matched. It can be seen that the matching significantly reduces the sample bias and enhances the similarity of the characteristics of the two groups of samples, indicating that the two groups of samples after matching are well-balanced.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eError reduction before and after matching for each variable\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSample\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eaverage value\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDeviation reduction\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e\u003cem\u003eT\u003c/em\u003e-test\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etreatment group\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003econtrol group\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eT\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026gt;|\u003cem\u003et\u003c/em\u003e|\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.527\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.564\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-5.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.23\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfter Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.528\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.527\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.965\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChronic disease status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Match\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAfter Match\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-539.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Match\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.465\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.408\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.464\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.435\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e48.7\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.174\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMedical insurance\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch Before\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.973\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.951\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.80\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.073\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.972\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.970\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePension insurance\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch Before\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.190\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.203\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.192\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAlcohol consumption\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch Before\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.4\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.68\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch Before\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.501\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.9\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.36\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch Before\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1238.6\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePolitical profile\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch Before\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.088\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-3.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.50\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMatch After\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.078\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84.1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Effect of mutual support on mental health and physical health status of elderly people\u003c/h2\u003e \u003cp\u003eIn order to test the robustness of Propensity Score Matching (PSM) results in this study, three different methods i.e., Near Neighbor Matching, Radius Matching and Kernel Matching were used to estimate the effect. And the average treatment effect ATT of the treatment group was used to indicate the effect of the impact, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.After the propensity score matching PSM analysis, all three matching methods have a significant impact on the mental health and physical health of rural Chinese older adults. For the mental health of rural older adults, participation in mutual care significantly negatively affects their ability to perform activities of daily living with a net effect of 0.020 to 0.027. For the physical health of rural older adults, the PSM results show that participation in mutual care significantly negatively affects the ability to perform activities of daily living of older adults, with a net effect of -0.029 to − 0.03.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMental Health of Rural Older Adults ATT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreat\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATT\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS.D\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual retirement behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeighborhood Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.366\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.72*\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadius Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.386\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.53**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKernel Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.358\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.47**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAbility to perform activities of daily living for the elderly in rural areas ATT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreat\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATT\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS.D\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual retirement behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeighborhood Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.73***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadius Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-3.02***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKernel Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.96***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Heterogeneity test\u003c/h2\u003e \u003cp\u003eHealth status can largely affect older people's participation in mutual aid for the elderly. Therefore, exploring the heterogeneity of impacts across different types of older people can enrich the existing literature on the impact of mutual care on the physical and mental health of rural older people. Here, the samples were grouped and processed to assess the between-group differences in the impact of chronic disease conditions, using the presence or absence of chronic disease as a marker.\u003c/p\u003e \u003cp\u003eHeterogeneity tests show that for older people who do not suffer from chronic diseases, the impact of mutual aging on their mental health and physical health is not significant under any of the three matching methods. In contrast, for rural older adults with chronic diseases, mutual care has a significant effect on their mental health and physical health under all three matching methods. The maximum net effect of mutual aid in old age on the mental health of rural elderly with chronic diseases is 0.03, and the maximum net effect of the effect on physical health is -0.035. See Tables\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, \u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e, and \u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMental Health of Rural Older Adults without Chronic Disease\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTreat\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eATT\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eS.D\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-V alue\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual retirement behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNeighborhood Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRadius Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.13\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKernel Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.360\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysical Health of Rural Older Adults without Chronic Disease\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreat\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATT\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS.D\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-V alue\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual retirement behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeighborhood Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.024\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.41\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadius Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.020\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.19\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKernel Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.022\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-1.136\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMental health of rural elderly with chronic diseases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreat\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATT\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS.D\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-V alue\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual retirement behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeighborhood Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.04**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadius Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.24**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKernel Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.20*\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhysical health of rural elderly with chronic diseases\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTreat\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eATT\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eS.D\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e-V alue\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMutual retirement behavior\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeighborhood Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.031\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.31**\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadius Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.314\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.035\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.72***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKernel Matching\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.034\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-2.67***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Discussion","content":"\u003ch2\u003e3.1 Low participation rate of rural elderly in mutual aid in old age behavior\u003c/h2\u003e\u003cp\u003eThe results of the study show that the participation of rural elderly in mutual aid in old age behavior is low, only 30%. This result is the same as the findings of Liu Zhuo\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e and Wang Ruibin \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. This may be due to the fact that the rural elderly are influenced by the deep-rooted traditional culture of raising children to prevent old age, and believe that participation in mutual aid is the children's inability to old age to themselves, which not only causes the elderly to lose face, but also causes the children to be labeled as unfilial, which leads to the fact that, even if the elderly have the desire to participate in the idea of mutual aid in old age, they are forced to refuse to participate in mutual aid due to the secular world, so that the elderly are not willing to give more attention to the way of old age other than the children's family old age. As a result, they are reluctant to learn more about other forms of old-age care besides their children's family care, which ultimately leads to a lack of awareness of the mutual care model among the elderly. On the other hand, rural elderly in China generally have a low level of education and are susceptible to the influence of traditional family concepts, and therefore spend most of their time on household chores and taking care of grandchildren in their old age, which leads to the lack of conditions for rural elderly to participate in higher-level social activities and a low awareness of participation\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The sustained and healthy operation of the mutual aid elderly care model cannot be separated from the participation of the government, village committees, village sages, volunteers and other more social levels. However, as one of the most important roles at the grassroots level, \"village two committees\" have a limited role in organizing and guiding the elderly to participate in mutual care. \"As a bridge between the government and the countryside, village committees are one of the main organizers of rural mutual care. However, due to the impact of rural reforms and social changes, villages have been hollowed out seriously\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, and it is difficult for village-level organizations to play their due organizational functions and guiding roles in rural mutual care for the elderly. In addition, policies and regulations related to mutual care for the elderly have been introduced late and are not well targeted, and many local grass-roots governments have not allocated appropriate funds for the development of the elderly due to a lack of awareness of their responsibilities, while the collective and community support for and investment in mutual care for the elderly are often influenced by the attitude of local governments.\u003c/p\u003e\u003ch2\u003e3.2 Participation in mutual care significantly improves the physical health status of rural elderly people\u003c/h2\u003e\u003cp\u003eWhether analyzed from the perspective of the whole sample or from the perspective of the rural elderly with chronic diseases, participation in mutual care significantly improves the physiological health status of the rural elderly, a result consistent with the study of Wu Qiaoli \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. Mutual care in essence focuses on the elderly, they are both service providers and service recipients Yi Zhiqi\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e, is the elderly in social activities to play their own strength to help each other, support each other \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e social behavior, rural elderly participation in mutual care to a certain extent, expanding the channels of their participation in social activities, the overall activity of the previously sedentary elderly has been increased!, whether it is simply getting out of the house or developing more regular physical activity habits. Additionally, increased activity can help to reduce adverse health effects such as smoking and increased body mass\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, and can significantly prevent the onset of disability in older adults\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. To a certain extent, the health care services provided by mutual care for the elderly can raise the level of health awareness among the elderly, help them to take the initiative and spontaneously change their lifestyles and habits, and develop a correct perception of recreation and health care, thereby reducing the level of risk of illness and minimizing the number of visits to the doctor.\u003c/p\u003e\u003ch2\u003e3.3 Participation in mutual care significantly reduces the mental health of rural older people\u003c/h2\u003e\u003cp\u003eAnalyzed from the perspective of the whole sample or from the perspective of rural older adults with chronic diseases, participation in mutual care significantly reduces the mental health status of rural older adults and increases the risk of depression among rural older adults. This finding breaks with the original preconceptions and is also inconsistent with some previous studies \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Possible explanations are that geography is a transmission of blood ties, and the social network of acquaintances in which traditional rural areas are situated provides a social foundation for rural mutual care\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e, and the social network is an informal institution that contains rich resources for old age\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Trusting relationships based on family ties play a key role in social networks\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e, however, some studies have indicated that family ties are the main reason for the high prevalence of depression in the elderly population\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Children in some families consider mutual support as a way of old age that makes them 'lose face'\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e.\" Children are the most important part of the social support system of the rural left-behind elderly\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e, but with the accelerated rate of urbanization, the number of children working outside the home has increased, the number of rural left-behind elderly has increased\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e, and the children's investment in the elderly, such as emotional support and economic support, has decreased. At the same time, with the continuous development of modern science and technology, the rural elderly are constantly disconnected from society, resulting in a sense of inferiority, and the rural elderly are difficult to achieve independence in emotional comfort \u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. In addition, the elderly have a certain enthusiasm to participate in mutual care in the short term, but they do not have a strong sense of cooperation, and in the long-term practice, due to the lack of timeliness of mutual service feedback, fairness is difficult to effectively measure and other issues, they will still produce individual negative consciousness due to the reality of conflict of interest\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. When living in mutual aid nursing homes, some of the elderly often have disputes due to different personalities, social experiences and values, causing psychological pressure on both sides, which is not conducive to the physical and mental health of the elderly \u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Social phenomena such as aging, empty nesters, and separation of the young and the old are gradually aggravated. In order to reduce the social pressure of young people, the elderly will stay home to take care of their grandchildren, and even take out their own pensions and retirement pensions to help their children to ease the economic pressure. Under this double pressure, the elderly will be in an unhappy mood even if they participate in mutual help for the elderly. At the same time, the elderly who suffer from chronic diseases, because chronic diseases have the characteristics of prolonged illness, multiple organ complications, high rate of disability and death, the need for long-term treatment and care, and high treatment costs, especially those who suffer from a variety of chronic diseases at the same time, the disease itself and the pressure it brings in terms of economy, care, and spirit, etc. \u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e which seriously affects the mental health status of the elderly.\u003c/p\u003e\u003ch2\u003e3.4 Suggestions\u003c/h2\u003e\u003cp\u003eFirst: Improve laws and regulations, establish a long-term feedback mechanism, and create a favorable external environment for the implementation of mutual aid for the elderly.\u003c/p\u003e\u003cp\u003eCarefully summarize the experiences of various regions in carrying out mutual aid for the elderly; strengthen the training of rural elderly service personnel through the opening of special professional courses, training programs, and free or subsidized training; and collaborate with a variety of educational and professional service organizations to achieve the sharing of resources and talents, and to alleviate the problem of human resource shortages in rural society. Strengthen collaboration with hospitals, schools, nursing homes and other organizations to carry out various forms of exchanges and training, to continuously improve the overall quality of the service team and enhance the quality of elderly services. At the same time, it can also actively collaborate with community and volunteer organizations to mobilize more social forces to provide support for the elderly.\u003c/p\u003e\u003cp\u003eSecond: Accelerating the cultivation of a new type of elderly care culture to promote diversification and sustainable development.\u003c/p\u003e\u003cp\u003eWith the help of the Internet and community publicity on mutual aid for the elderly, the elderly are gradually getting rid of their dependence on traditional ways of ageing; the culture of filial piety is publicized, and children are advocated to participate in mutual aid for the elderly as volunteers, so as to combine ageing at home with mutual aid for the elderly; the mutual aid method of combining \"labour and support\" is implemented, and the elderly in special hardship and the low-income elderly are encouraged to do some free, low-paid labour at the Happy Court. It also promotes the \"labor-support\" combination of mutual aid, encouraging the elderly in special hardship and the low-income elderly to do some free, low-paid labor in the Happiness Courts. On the other hand, the elderly, especially those who are able to take care of themselves, should abandon the notion that they are the ones being helped and realize that their skills, life experience and human resources can still produce social value; on this basis, a model of mutual assistance for the elderly in the rural community has been proposed in order to provide diversified, high-quality services for the elderly.\u003c/p\u003e\u003cp\u003eThird: Paying attention to the mental health of the elderly\u003c/p\u003e\u003cp\u003eWhen arranging for the elderly to live in a home, consider their personality, sleeping habits, and hobbies to meet their living and spiritual needs; encourage and advocate the participation of nursing, doctors, mental health counselors and other professionals in mutual care, improve the rural health care system, and improve the quality of mutual care services; increase the space for the elderly to improve their self-care activities; improve the quality of the elderly's care, and integrate medical care with mutual care. (c) Combining medical care with mutual support for the elderly, and emphasizing and preventing the possible effects of chronic diseases on the elderly.\u003c/p\u003e\u003ch2\u003e4 Limitations and Future Research\u003c/h2\u003e\u003cp\u003eThe data in this article uses only one year of cross-sectional data, which is a short observation period. Therefore, panel data for multiple years can be included in subsequent studies so that validation analyses can be conducted using more and more comprehensive indicators.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthors' contributions: Bin Hu proposed the research idea, designed the research propositions and controlled the quality of the final paper; Xiaohan Liu, Guangyao Liu, and Jialiang Liu completed the writing of the paper's data, the data organization, the statistical processing, and the graph drawing.\u003c/p\u003e\u003cp\u003eData Availability Statement: The data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eQi Chen. Silver-haired economy calls for diversified supply [N]. Economic Herald,2024-01-08(001).\u003c/li\u003e\n\u003cli\u003eQi Ling. 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General Practice Nursing,2020,18(10):1186-1188.\u003c/li\u003e\n\u003cli\u003eYAN Hong,LIU Shuwen. Current situation and influencing factors of mental health of chronically ill older adults[J]. Chinese Journal of Gerontology,2019,39(21):5366-5369. \u003c/li\u003e\n\u003cli\u003eHAN Huiran,XU Lingyi,YANG Chengfeng. Impacts of multi-scale built environment on mental health of the elderly - empirical evidence from Hefei based on extreme gradient enhancement model[J]. Geography Research,2024,43(06):1502-1521.)\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mutual aid for the elderly, Rural elderly, Physical health, Mental health, Propensity score matching","lastPublishedDoi":"10.21203/rs.3.rs-4898207/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4898207/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTo study the impact of mutual care on the physical and mental health of rural elderly, and provide countermeasures and suggestions for the long-term development of mutual care.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMETHODS: Data from the 2018 China Health and Aged Care Tracking Survey (CHARLS) were selected from 8,369 elderly people aged ≥60 years old, and propensity score matching (PSM) was carried out using STATA (MP17) software using nearest-neighbor matching, kernel matching, and radius matching, and then heterogeneity was used to analyze the mean effect values among different populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRESULTS: The results of propensity score matching PSM showed that participation in mutual care had a significant positive effect on the mental health of the rural elderly, with a net effect of 0.020~0.027, and a significant negative effect on the physical health of the rural elderly, with a net effect of -0.029~-0.030. Heterogeneity analyses showed that participation in mutual care had no significant effect on the physical and mental health of the rural elderly who did not suffer from chronic diseases. Physical and mental health does not have a significant effect. The net effect is -0.06031 to -0.035, and the net effect is 0.029 to 0.030.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion: the rate of rural elderly people's participation in mutual aid is low, and participation in mutual aid has different degrees of influence on the physical and mental health of rural elderly people, and different characteristics of rural elderly people's participation in mutual aid have different degrees of influence on their physical and mental health.\u003c/p\u003e","manuscriptTitle":"Research on the Impact of Mutual Elderly Care on the Physical and Mental Health of Rural Elderly--An Empirical Study Based on the Propensity Score Matching Method (PSM)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-19 08:24:23","doi":"10.21203/rs.3.rs-4898207/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-09T06:38:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-07T12:03:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-22T18:59:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"229568608298345037780319122792691689201","date":"2024-09-10T09:00:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188273331969308674902904449978173388758","date":"2024-09-08T11:51:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-08T08:17:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-27T06:34:51+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-08-22T07:39:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-21T08:46:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-08-12T07:00:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"833a2610-c6c2-4a47-9007-40c14aadf206","owner":[],"postedDate":"September 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-20T16:04:32+00:00","versionOfRecord":{"articleIdentity":"rs-4898207","link":"https://doi.org/10.1038/s41598-025-85305-7","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-01-17 15:58:00","publishedOnDateReadable":"January 17th, 2025"},"versionCreatedAt":"2024-09-19 08:24:23","video":"","vorDoi":"10.1038/s41598-025-85305-7","vorDoiUrl":"https://doi.org/10.1038/s41598-025-85305-7","workflowStages":[]},"version":"v1","identity":"rs-4898207","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4898207","identity":"rs-4898207","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}