Abstract
Using data from the 2018 China Health and Retirement Longitudinal Study (CHARLS), this research probed into the effects of land circulation on the elderly physical health and mental health and their underlying mechanisms. The results revealed that land circulation has a significant positive impact on the health of the elderly, but this health-promoting effect is mainly on mental health, while the impact on physical health is not significant. Moreover, the two different effects still hold after addressing endogeneity using the propensity score matching method and the instrumental variables method. Also, the health effects of land circulation differ in terms of gender, age, and two-generation living arrangement, that is, land circulation significantly strengthens the mental health of the lower-aged elderly, males, and the elderly living with their children. Additionally, the mechanism analysis showed that the increase in non-farm income and social interaction frequency is a vital channel of land circulation affecting the mental health of the elderly. Thus, the land circulation system should be further standardized, and the circulation mechanism for the rural elderly population should be continuously established and improved, thereby effectively bringing into play the health-promoting effects of land circulation.
Keywords: Chinese elderly people, Land circulation, Physical health, Mental health
Subject terms: Risk factors, Quality of life
Introduction
According to the World Health Organization, the percentage of individuals aged 60 and over in China is expected to increase from 12.4% in 2010 to 28% by 2040. As China’s population ages rapidly, the health of the elderly has become a significant social concern. Both physical and mental health are crucial not only for the quality of life of the elderly but also in addressing various issues related to aging within families and society as a whole. Globally, there is inadequate evidence suggesting that the elderly are healthier than their parents at present1, which is particularly prevalent in rural areas, where outdated healthcare systems and a lack of public services, such as medical care, contribute to the problem. Data from the Seventh National Population Census indicates that the overall health status of the elderly in rural areas is 83.9%, which is significantly lower than the 91.64% health status found among the elderly in urban areas. In 2016, the Chinese government issued the “Healthy China 2030” planning outline, which aims to achieve universal health. This initiative emphasizes the need to gradually reduce the disparities in basic health services and health levels between urban and rural areas, with a particular focus on improving conditions at the rural grassroots. The key to promoting health equity for the elderly in urban and rural areas lies in improving the health of rural older people. It is essential to thoroughly understand their health status and the factors that influence it.
In terms of factors influencing health in old age, studies have focused on the effects of individual characteristics2, socioeconomic status3, and health insurance4 on the physical and mental health of the elderly. However, there is a relative paucity of explorations on the effects of land circulation on the physical and mental health of rural older people. In fact, with the acceleration of urbanization, industrialization, and agricultural modernization in China, land circulation has become an important trend in rural development. Land circulation not only concerns the restructuring of the rural economy and the improvement of production efficiency, but also has a profound impact on the lifestyles, economic resources, and physical and mental health of the rural elderly. In earlier studies, You et al. (2013) pointed out that land circulation did not have a positive effect on the health status of family members due to the pressure of survival and changes in employment space5. But Ma et al. take a different view, they argued that the rise in income from land circulation can improve the health of farm households6. Liao et al. found that land circulation can reduce the psychological and health affiliation of farm households by constructing a welfare indicator system for transferred households7. Most of these studies consider health as an aspect of farm household welfare and only analyze the average impact of land circulation on farmers’ health in general terms, without taking into account the variability in the health status of household members. On this basis, Li et al. further analyzed the impact of land circulation on the physical health of rural middle-aged and elderly people using data from the China Healthy Aging and Tracking Survey8. They pointed out that land circulation has an important impact on the physical health of middle-aged and elderly people.
Agricultural production in China is labor-intensive, intensive and demanding, which inevitably places a heavy burden on the physical and mental health of farmers. At the same time, due to the lack of a retirement protection system for agricultural laborers, many rural elderly continue to engage in heavy agricultural production activities even after reaching “retirement” age. With the implementation of the land circulation policy, rural elderly people will have the opportunity to choose to circulate their land contract management rights to others, which has become a form of “retirement” for them in a certain sense9. Theoretically, land circulation will promote the physical and mental health of the elderly. On the one hand, the land circulation can liberate older people from heavy agricultural production and reduces the time spent on agricultural labor, which reduces the depletion of health stock by alleviating time constraints. On the other hand, the increase in income brought about by land circulation can effectively increase the budgetary constraints on health investment by the elderly. However, at present, China’s land circulation mechanism is imperfect, and how to deal with the aging problem of rural population is not well considered at the policy and implementation level10, which seriously hinders land circulation. In order to further promote the orderly circulation of land, it is necessary to continuously enrich the research on the impact of land circulation on the elderly. Based on this, this paper concentrates on the effects of land circulation on the physical and mental health of the elderly and its internal mechanism on the basis of existing studies. Clarifying the health-promoting effects of land circulation is not only conducive to the realization of healthy aging, but also more conducive to the development of agricultural modernization.
Despite the compelling evidence linking land circulation to the health of older people, the research that has been conducted in the current context is limited in the following ways. First, existing research in this field primarily considers health as one of the numerous dimensions for measuring the welfare of rural households, while lacking a focus on elderly individuals in rural areas. Under the realistic background of the aging situation of the rural labor force in China, the land circulation behavior of the elderly group deserves more attention. Second, existing academic research on the health of the elderly has primarily focused on analyzing a single health aspect, with few studies incorporating both physical and mental health into a unified analytical framework. Although a limited number of recent studies have attempted to integrate these two dimensions, they have struggled to address endogeneity issues in their empirical analyses effectively. For example, Li et al. employed a Probit and IV model to assess how land circulation affects the health of middle-aged and elderly individuals8.However, they paid insufficient attention to mental health. Moreover, the methodology used in their study did not adequately address the potential issue of self-selection bias. This is important to consider, as the decision of older individuals to circulate their farmland constitutes a non-random “self-selecting behavior.” Consequently, there remains uncertainty regarding whether land circulation can positively influence health outcomes in old age.
This study uses CHARLS 2018 to analyze the impact of land circulation on the physical and mental health of the elderly. Although it is not a long panel of microdata to observe its long-term and dynamic impact effects, the strategy of reference to existing empirical studies is chosen to construct a counterfactual framework by using the Propensity Score Matching (PSM) method to maximise the elimination of sample bias and to solve the sample endogeneity problem by means of instrumental variables. The research is constructed as below: Sect. "Theoretical analysis and research hypotheses" focuses on the theoretical analysis; Sect. "Methods" demonstrates dataset and the econometric methodology; Sect. “Results” shows and analyzes the empirical findings; Sect. "Discussion" is the discussion; Sect. "Conclusions" summarizes the conclusions.
Theoretical analysis and research hypotheses
Land circulation and physical and mental health in old age
Grossman first constructed the theoretical analytical model of health needs from an economic perspective, which assumes that human beings are born with an initial stock of health that depreciates with age, whereas it can also be improved via investments in health, such as a healthy lifestyle11. For the elderly, especially the rural elderly, even if they have reached the age of “retirement”, they continue to engage in heavy agricultural production activities, and this form of production in elderly agriculture is essentially a low-level deficiency need12, which is at the expense of their own health13,14. This is because the specificity of agricultural production and the hardship of the labor environment will more dramatically accelerate the depletion of the health stock of the elderly, thus exacerbating the health problems of the elderly. Especially in the season of heavy agricultural work such as spring planting and fall harvesting, long hours of field labor lift the incidence of injury and illness among rural elderly15. Although the popularity of agricultural mechanization and outsourcing of production services can effectively reduce the physical intensity, concerning the reality of the rising price of services and the high cost of labor supervision, the demand of farmers is inhibited to a certain extent16. In addition, as is known to everyone, agriculture is a weak industry with both natural and market risks, which is extremely vulnerable to various natural disasters and market fluctuations. At the same time, the plight of “no harvest” or “increased production but no increase in income” occurs from time to time, damaging the physiological health of the elderly agricultural workers. However, the loss of physical health of the elderly farmers is not only not compensated by the material level, but also brings about the loss of spiritual level. Land circulation can affect the health stock of the elderly to a great extent. On the one hand, the steady increase in income brought by land circulation can increase the budgetary constraints of the elderly on health investment, and then increase the saving of health stock. On the other hand, land circulation can not only reduce the time and intensity of agricultural labor of the elderly but also effectively mitigate their psychological anxiety about the fluctuation of food prices and natural disasters, thus slowing down the depletion of their own health stock. Based on this, this study proposes the following hypotheses:
H1a: Land circulation has a positive impact on the mental health of the elderly.
H1b: Land circulation has a positive impact on the physical health of the elderly.
Mechanisms of land circulation on the physical and mental health of the elderly
The current land circulation in China is mainly divided into Intra-circle trading based on human relationships and peripheral trading based on market prices17. The former is mostly embedded in the social network of human relations, with strong informality. As revealed by the rational economic person assumption, low or zero rent for transferring out households is not free in the substantive sense but is exchanged for non-monetary benefits such as caring for the old and weak, production and life assistance18, thus allowing for an effective response to the risks stemming from insufficient social security. Numerous studies have indicated that “favor rent” is widely present in the land circulation market19,20, accounting for up to 70%21. It can be seen that land circulation strengthens the social relationship network of farmers to a certain extent and promotes close ties between farmers. The social attributes of human beings determine that social interactions significantly affect human psychological traits and behavioral habits22–24. In the case of the rural elderly, firstly, participation in land circulation provides more material and non-material support (e.g., health-care information) from interpersonal interactions outside the family system, which in turn consolidates their ability to fight diseases and improves their physical health. Second, in the reality of the weakening of traditional family old-age security, the external support provided by informal social interactions with relatives, friends, and neighbors is also a vital source of social security for the rural elderly, which benefits the reduction of health risks in old age. Finally, regarding social participation, land circulation can reduce the time spent by the elderly in production and labor, and they will have more leisure time to participate in social activities, which is the most direct way to satisfy their social needs and enhance their sense of belonging to society, and it can effectively alleviate their psychological anxiety and ill-health. In conclusion, the socialization effect brought about by land circulation is an important way for the elderly to acquire health support from the external system of the family.
From the viewpoint of the internal system of the family, land circulation can also effectively optimize the allocation of family labor resources, facilitate the transfer of family members to the non-farm sector with higher labor remuneration, and increase the non-farm income of farm households. This view has basically reached a consensus in the academia25,26. Furthermore, the level of income is also a key factor affecting the physical and mental health of the elderly27–29. For this reason, the impact of income on the health of the elderly is not limited to access to health resources and services but also has a significant impact on the psycho-emotional well-being of the elderly. Specifically, first, improved income levels can alleviate the financial liquidity constraints faced by rural households, raising their standard of living and increasing budgetary constraints on health investments (e.g., by increasing the terms of health care payments). Second, the social attributes of human beings lead people to inevitably compare their own family’s income with that of others, and when theirs is lower, it will exacerbate their sense of relative psychological deprivation, and make them prone to negative emotions such as frustration and depression. Especially in the rural acquaintance society centered on kinship ties and vernacular circles, this adverse effect is more prevalent and stronger30. It is thus clear that the income-generating effect of land circulation is not only effective in promoting the intrinsic demand of the elderly for products and services that maintain their health but also in enhancing their satisfaction with life.
Based on the above analysis, this study proposes the following research hypotheses:
H2a: Land circulation can increase the social interaction of the elderly and thus promote their physical and mental health.
H2b: Land circulation can increase the off-farm income of older farmers and thus promote their physical and mental health.
Methods
Data source
The data used in this study are from the China Health and Retirement Longitudinal Survey (CHARLS) 2018.The survey focuses on middle-aged and elderly households and individuals aged 45 and older in China, aiming to obtain high-quality micro-data to analyze the issue of population aging. The major reasons for selecting this database are as follows. First, the survey program provides a more comprehensive measure of the physical and mental health of the elderly, which helps to objectively and comprehensively identify the physical and mental health of the elderly. Second, it provides more detailed information on the production and asset status of elderly farmers’ families, which can effectively identify the land circulation behavior of elderly farmers. Currently, the latest data is updated to 2018, and thus this study also adopts the latest available 2018 survey data and selects rural (agricultural household) elderly aged 60 and above as the sample, with a total of 3,250 valid samples after deleting missing values and outliers.
Variable selection
Dependent variables
The WHO proposes that health is the organic unity of physical health and mental health. In view of this, the current study characterizes the health status of the elderly from two dimensions: physical health and mental health. For one thing, mental health is manifested by respondents’ scores on the Depression Self-Assessment Scale (CES-D10), which consists of a total of 10 questions asking respondents about their subjective feelings and behaviors in the previous week, such as whether they were depressed. For another, physical health is reflected by the scores of the Self-Assessment of Daily Living Abilities of the Elderly Scale (ADL), totaling 6 questions, which mainly ask the respondents about their abilities necessary to maintain a basic life, covering 6 activities such as waking up independently, eating, and going to the toilet. Notably, mental health and physical health are both negative indicators, that is, the higher the score, the poorer the health of the elderly (Supplementary Table S1).
Independent variables
The core explanatory variable in this study is land circulation, which is measured using the CHARLS questionnaire, “In the past year, have you and your spouse rented out your farmland, forest land, pastureland, or water pond to others?” This question is measured by assigning a value of 1 if it is “yes” and 0 if it is not.
Mechanism variables
This study selects the two variables of non-farm income and social interaction as the mechanism variables of the impact of land circulation on the physical and mental health of the elderly, where the social interaction variable is based on the question “Did you engage in any of the following activities in the past month?”, including 10 activities such as hanging out, socializing with friends, etc. The elderly are assigned a value of 1 for participating in any of these, and 0 for the opposite. Additionally, the income-generating effect of land circulation is mainly derived from a rise in non-farm income. Accordingly, this study adopts the average non-farm income status of household members to characterize the income-generating effect of land circulation.
Control variables
In order to control the influence of other variables on the physical and mental health of the elderly as much as possible, this study refers to existing studies8,31 and the factors of the elderly’s individual characteristics, behavioral habits, and family status were included as control variables. Specifically, the level of individual characteristics was selected as age, gender, education, marital status, chronic disease, health insurance, regular exercise, and personal income were selected at the level of personal characteristics, and the number of family members, number of children, intergenerational care, indoor cleanliness, and whether they lived with their children were controlled at the level of family characteristics. Several studies have shown that caring for grandchildren can help older people maintain their cognitive abilities by providing positive experiences32–34. A tidy indoor environment can reduce the accumulation of dust, bacteria, and viruses, which in turn lowers the risk of illness for elderly individuals. Furthermore, a clean and organized space can promote feelings of happiness and relaxation, helping to alleviate negative emotions such as anxiety and depression in older people. Specific descriptive statistics for the variables are shown in Table 1.
Table 1.
Variable definitions and descriptive statistics.
| variables | Variable definition and assignment | Mean | Std |
|---|---|---|---|
| Dependent variables | |||
| Mental health | Mental health score, negative indicator | 9.3421 | 6.7888 |
| Physical health | Physical health score, negative indicator | 0.6332 | 1.5908 |
| Independent variables | |||
| Land circulation |
Whether the land was transferred out: yes = 1, no = 0 |
0.2462 | 0.4308 |
| Mechanism variables | |||
| Socialization | participation in social activities = 1, no participation = 0 | 0.4591 | 0.4984 |
| Non-farm income | Per capita household non-farm income (yuan, plus 1 to take the natural logarithm) | 7.2616 | 1.4886 |
| Control variables | |||
| Age | Actual age of the elderly (years) | 67.4726 | 5.5939 |
| Gender | Male = 1, Female = 0 | 0.5071 | 0.5000 |
| Education | Education level:illiterate-PHD:1–9① | 2.7455 | 1.6672 |
| Marital status | Married = 1, unmarried, divorced or widowed = 0 | 0.8468 | 0.3603 |
| Medical insurance | Yes = 1, no = 0 | 0.9757 | 0.1541 |
| Chronic disease | Yes = 1, no = 0 | 0.8606 | 0.3464 |
| Exercise | Yes = 1, no = 0 | 0.8126 | 0.3903 |
| Personal income | Personal income plus 1 takes the natural logarithm | 6.4908 | 2.7045 |
| Population size | Number of people in the household | 2.7246 | 1.4446 |
| Number of children | Number of living children | 2.9865 | 1.2960 |
| Intergenerational care | Caring for grandchildren = 1, otherwise = 0 | 0.4388 | 0.4963 |
| Elderly children living together | Yes = 1, No = 0 | 0.3335 | 0.4715 |
| Indoor cleanliness | Clear, very clear and excellent = 1, otherwise = 0 | 0.5751 | 0.4944 |
| N | 3250 | ||
①Education level: illiterate = 1, did not finish primary school = 2, sishu/home school = 3, elementary school = 4, middle school = 5, high school/vocational school = 6, two-/three-year college/associate degree = 7, four-year college/Bachelor’s degree = 8, Master’s degree/PHD = 9.
Research methods
Seemingly unrelated model (SUR)
The independent variables 
and 
in this paper are the mental health and physical health of the same elderly individuals, which are closely related. In other words, there may be a problem of high correlation of the dependent variable in the model, which results in the two regression equations corresponding to the perturbation term being correlated. In this regard, this paper drew the study35 and used SUR to jointly estimate the two equations at the same time in order to improve the estimation efficiency.
 |
1 |
The SUR model is:
 |
2 |
where, 
is 
of individual 
, 
characterizes whether land is transferred, 
is the individual characteristics of the elderly such as gender, age, education and other characteristics of the family variables, 
is a random perturbation term. in the Eq. (2), 
includes the control variables and random perturbation terms.
Propensity score matching (PSM)
In fact, when the elderly consider whether to participate in farmland, they need to take into account the influence of their own, family and other factors, while the random disturbance term 
may also include other unobservable factors affecting land circulation and the physical and mental health of the elderly at the same time. In other words, whether or not the elderly circulate their land is a non-random “self-selected behaviour”. Simple OLS models tend to bias the estimation results. Therefore, in order to effectively solve the sample self-selection problem and ensure the reliability of the empirical results, this study further used PSM proposed by Rosenbaum36 in 1983 to estimate the Average Treatment Effect on the Treated (ATT) on the physical and mental health of the elderly.
PSM is a kind of “counterfactual estimation”, the main idea is to put the selection of elderly people who participate in land circulation and those who do not participate in land circulation in a random state, and find a control group that does not participate in land circulation for the treatment group that participates in land circulation with very similar characteristics, and then compare the results of the treatment group and the control group, and the difference is ATT. In this study, the dummy variable 
is used to indicate whether the rural elderly participate in the circulation of land or not, where 1 is the treatment group and 0 is the control group; the physical and mental health scores of the rural elderly are denoted as 
. The treatment effect of 
on 
is:
 |
3 |
where, 
denotes the physical and mental health scores of the elderly who participated in land circulation, 
denotes the physical and mental health scores of the elderly who did not participate in land circulation, and 
denotes the treatment effect of the impact of the participation in land circulation on the physical and mental health of the elderly, that is:
 |
4 |
 |
5 |
Then the “participant average treatment effect” is:
 |
6 |
In terms of the selection of matching methods, it is not yet clear in the literature which matching method is the most effective. Consequently, to guarantee the robustness of the matching, this study adopts five common matching methods, which are k-nearest neighbor matching, caliper matching, intra-caliper nearest neighbor matching, kernel matching, and local linear regression matching respectively. All of the matching methods adopted are with put-back matching.
Results
As can be seen from Fig. 1, the health status of the elderly in the land circulation group is better than that in the non-circulation group(Based on the variable definition section, the land circulation referred to in this paper specifically means land transfer-out). Higher scores represent poorer levels of physical and mental health. The average values of physical health and mental health of the elderly in the land circulation group are 8.8888 and 0.57 respectively, while the average values of the non-circulation group are 9.4902 and 0.6539. In both physical and mental health dimensions, the mean values of the non-circulation group are larger (indicating poorer health), whereas those of the land circulation group are smaller (indicating better health). Therefore, it can be preliminarily judged that land circulation is associated with better physical and mental health outcomes for the elderly, based on the lower average scores in this group.
Fig. 1.
Physical and mental health of the elderly (land circulation and non-circulation).
Baseline regression
Table 2 reports the estimation results of the impact of land circulation on the physical and mental health of the elderly. The P-value of “no contemporaneous correlation” between the perturbation terms of the system of linked equations is 0.0000, revealing that the model rejects the original hypothesis that the perturbation terms of the equations are independent of each other at the 1% level, and confirms that the systematic estimation using the SUR can promote the estimation efficiency. From the regression results, the effect of land circulation on the mental health of the elderly is significantly negative regardless of the inclusion of control variables, indicating that the participation of the elderly in land circulation can significantly lift their mental health status. Despite this, the effect of land circulation on the physical health of the elderly does not pass the significance test, but the coefficient is negative. One possible reason for this is that compared with mental health, the physical health status of the elderly is the result of the long-term accumulation of various factors like the economy, personal lifestyle and habits, etc. In the subsequent study, cross-period panel data is used to figure out the impact of land circulation on the physical health of the elderly. Research hypothesis 1a is preliminarily tested, and hypothesis 1b is not tested.
Table 2.
Benchmark regression estimation results.
| Mental health (Negative indicators) | Physical health (Negative indicators) | |||
|---|---|---|---|---|
| (1) | (2) | (3) | (4) | |
| Land circulation | − 0.6015** | − 0.6146** | − 0.0839 | − 0.0945 |
| (0.2763) | (0.2652) | (0.0648) | (0.0626) | |
| Age | − 0.0460* | 0.0249*** | ||
| (0.0242) | (0.0057) | |||
| Gender | − 1.4890*** | − 0.0994* | ||
| (0.2548) | (0.0601) | |||
| Education | − 0.4048*** | − 0.0321* | ||
| (0.0761) | (0.0180) | |||
| Marital status | − 1.3198*** | − 0.1674** | ||
| (0.3362) | (0.0793) | |||
| Medical insurance | 1.0718 | − 0.3191* | ||
| (0.7455) | (0.1759) | |||
| Chronic disease | 2.8958*** | 0.4721*** | ||
| (0.3307) | (0.0780) | |||
| Cxercise | − 0.7339** | − 0.6446*** | ||
| (0.2950) | (0.0696) | |||
| Personal income | − 0.1415*** | − 0.0437*** | ||
| (0.0428) | (0.0101) | |||
| Population size | − 0.2112** | 0.0005 | ||
| (0.0910) | (0.0215) | |||
| Number of children | 0.1741* | 0.0551** | ||
| (0.0969) | (0.0229) | |||
| Intergenerational care | 0.3255 | 0.0673 | ||
| (0.2478) | (0.0585) | |||
| Elderly children living together | 0.2519 | − 0.0263 | ||
| (0.2721) | (0.0642) | |||
| Indoor cleanliness | − 1.1148*** | − 0.1014* | ||
| (0.2323) | (0.0548) | |||
| constant | 9.4902*** | 14.0254*** | 0.6539*** | − 0.1604 |
| (0.1371) | (1.8844) | (0.0321) | (0.4446) | |
| N | 3250 | 3250 | 3250 | 3250 |
* p < 0.10, ** p < 0.05, *** p < 0.01, robust standard errors in parentheses. Same below.
In terms of control variables, the regression coefficients of individual features of the elderly including gender, education level, and marital status on mental health and physical health are all significantly negative, suggesting that the elderly who are male, have high levels of education, and have a spouse (who is alive) will have better mental health and physical health. Among them, male older people have better physical and mental health than females, which can be attributed to the fact that women are usually more strenuous in their daily lives, and are more likely than males to report mobility problems, pain, and psychological distress accumulation in the short and long term. This is in line with the findings of Homan and others37. In addition, the physical and mental health of older adults who have no chronic diseases, exercise frequently and have high income will be better than those who have chronic diseases, exercise less frequently, and have low or even no income. This is because older adults with personal income will have a stronger sense of self-actualization and value, and will be less likely to have negative emotions and psychological stress. Finally, the number of children and the cleanliness of the house also significantly affect the physical and mental health of the elderly.
Propensity score matching analysis
Common support hypothesis
The prerequisite for the estimation of the PSM method to be effective is that the propensity scores of the treatment and control groups have a large overlapping region. In view of this, this study examined the common support domain after matching by plotting the density function graph. As depicted in Fig. 2 (caliper matching), after propensity score matching, there is a large overlapping area in the distribution of propensity scores between the samples whose cropland is transferred and those whose cropland is not transferred, indicating that the quality of sample data matching is better and the model satisfies the conditions of common support hypothesis.
Fig. 2.
Density function after propensity score matching.
Balance test
Another prerequisite for the estimation validity of the PSM method is that the matched treatment and control groups are not systematically different among the covariates, suggesting that there is a balance between the treatment and control groups. The standardized deviation below 20% between the matched treatment and control groups proposed by Rosenbaum (1985) is often taken as a criterion in research38. Thus, it is adopted in this research to test the balance of the model as well. First, the results of the covariate balance test show (see Fig. 3) that the standardized deviation of each covariate after matching is within 10%, which is significantly smaller than the 20% red line standard stipulated in the balance test, indicating that the matching effect is better, and the model satisfies the conditions of the balance test.
Fig. 3.
Comparison of standard deviation of covariates before and after matching.
Second, as shown by the results of the balance test in Table 3, after sample matching, the pseudo-R2, LR statistic, and deviation from the mean are reduced dramatically compared to the pre-matching period, and the propensity score matching significantly reduces the covariate differences between the treatment and control groups, again implying that the quality of sample matching is better.
Table 3.
Balance test results of explanatory variables before and after matching.
| Matching method | Pseudo-R2 | LR statistic | Mean value deviation(%) |
|---|---|---|---|
| Pre-match | 0.009 | 31.33 | 5.6 |
| Caliper matching(r = 0.05) | 0.002 | 4.46 | 1.9 |
| Near-neighbor matching in calipers (k = 4) | 0.001 | 1.42 | 1.5 |
| K-nearest neighbor matching (k = 4) | 0.002 | 3.38 | 2.2 |
| Nuclear matching | 0.002 | 3.63 | 1.7 |
| Local linear regression matching | 0.002 | 5.25 | 2.9 |
Impact effect measurement
According to Eq. (6), the ATT of the impact of land circulation on the mental health and physical health of the elderly is calculated, and the results are shown in Table 4. It can be found that the differences in ATT values obtained from the five matching methods are small, but the direction of the coefficients are all significantly negative, which again indicates good robustness of sample data. Specifically, after the PSM counterfactual estimation, land circulation significantly improves the mental health of the elderly, and the average net effect of the impact is -0.6174. This means that land circulation causes a significant decrease in the value of the mental health score of the elderly by 6.51% (The formula for calculating the growth rate is: Growth rate = ATT/control group mean*100%). Research hypothesis 1a is again tested. However, from the regression results, regardless of the matching method, the ATT value of physical health does not pass the significance test, which is consistent with the results of the baseline regression. That is to say, land circulation can significantly improve the mental health of the elderly, but does not have a significant effect on their physical health.
Table 4.
Mean treatment effects of land diversion on physical and mental health in old age.
| mental health | physical health | |||
|---|---|---|---|---|
| ATT | std | ATT | std | |
| Caliper matching(r = 0.05) | − 0.5716** | 0.2721 | − 0.0875 | 0.0615 |
| Near − neighbor matching in calipers(k = 4) | − 0.6625** | 0.3028 | − 0.0859 | 0.0685 |
| K − nearest neighbor matching(k = 4) | − 0.7774** | 0.3052 | − 0.1021 | 0.0688 |
| Nuclear matching | − 0.5694** | 0.2721 | − 0.0862 | 0.0614 |
| Local linear regression matching | − 0.5060* | 0.2782 | − 0.0838 | 0.0912 |
| Mean | − 0.6174 | 0.2861 | − 0.0891 | 0.0703 |
Heterogeneity analysis
The above empirical analysis shows the average effect of land circulation on the physical and mental health of the elderly, but the impact may vary among different elderly groups. Based on this, this research probed into group differences from three perspectives: age, gender, and whether they live with their children, in order to enrich the study of the impact of land circulation on the physical and mental health of the elderly, and the results are presented in Table 5.
Table 5.
Results of heterogeneity analysis.
| Mental health | Physical health | ||||
|---|---|---|---|---|---|
| Variables | Criteria for classification | ATT | Std | ATT | Std |
| Age | Younger age(< 70) | − 0.6457** | 0.3232 | − 0.0168 | 0.0662 |
| Larger age(> 70) | − 0.5898 | 0.5043 | − 0.2276* | 0.1323 | |
| Genders | Male | − 0.7173** | 0.3522 | − 0.0551 | 0.0791 |
| Female | − 0.5120 | 0.4010 | − 0.1221 | 0.0935 | |
| Generations living together | Living with children | − 1.0729** | 0.4675 | − 0.1331 | 0.1159 |
| Not living with children | − 0.3552 | 0.3338 | − 0.0595 | 0.0723 | |
At the age level, the data is divided into two groups of low and high age according to whether the elderly reach 70 years old or not. The results show that there is a significant difference in the impact of land circulation on the physical and mental health of the elderly of different ages and that this impact is more pronounced on the mental health of the elderly of low age, but for the elderly of high age, land circulation affects their physical health more prominently. The possible reason for this is that as age increases, the decline of human body functions is an inevitable trend, and for the elderly, engaging in agricultural production and management activities will cause more physical wear and tear, and thus land circulation can effectively improve their physical health. For the elderly, land circulation can increase the time of non-farming business, and then engage in higher-income jobs (According to the China Census Yearbook-2020, it is estimated that 37.56% of the lower-aged elderly (60–69 years old) are engaged in non-agricultural activities.) or activities with a higher value for personal emotions (e.g., intergenerational care for children and grandchildren, etc.). Thus, the effect of land circulation on mental health is more significant. From the gender perspective, participation in land circulation only significantly strengthens male elderly people’s mental health at the 5% level but has no significant impact on their physical health or the physical and mental health of female elderly people. In terms of the social division of labor, compared with women, men put more labor and time into agricultural production, and most studies have found that the life expectancy of men is shorter than that of women. Land circulation significantly enhances the mental health of the elderly who live with their children, but does not have a significant effect on the psychological health of the elderly who do not live with their children. Generally speaking, the elderly living under the same roof as their children can receive more daily care, especially in terms of mental comfort, which can effectively reduce the sense of loneliness among the elderly.
Endogeneity test
There may also be endogeneity due to reverse causality between land circulation and physical and mental health in old age, making the estimation results biased or non-consistent. At present, the instrumental variable to solve the endogeneity problem of the model is an effective method commonly used in domestic and international research. Consequently, this study draws on existing research39,40, selecting the level of land circulation at the village level as an instrumental variable for “land circulation”. Theoretically, whether a rural elderly transfers land is correlated with whether other households in the village are involved, and in an acquaintance society such as a rural village, there is a strong transmission and driving effect among residents. In turn, whether other elderly families transferred out of their land has little effect on their own level of physical and mental health, and thus, this variable satisfies the prerequisites for instrumental variable correlation and exogeneity. The test through Stata software yields that the LM statistic of the non-identifiable test is 608.742, corresponding to a P-value of 0.0000, which is significant at the 1% level, thereby strongly rejecting the original hypothesis of non-identifiable. The F-value of the weak instrumental variable is 1407.889, which is also significant at the 1% level. That is to say, the original hypothesis of the existence of a weak instrumental variable is rejected, and the above results further support the reasonableness of the instrumental variables selected in this study.
The regression results of using instrumental variables are shown in Table 6, and it is evident that the regression results using instrumental variables are consistent with the baseline regression results, that is, the health-promoting effect of land circulation is mainly reflected in mental health. In contrast, the effect on physical health is not significant. Thus, H1a is further validated, and H1b is still unvalidated, which suggests that the findings of this study are still robust after the endogeneity problem is overcome.
Table 6.
Regression results with the introduction of instrumental variables.
| Mental health | Physical health | |||
|---|---|---|---|---|
| Phase I | Phase II | Phase I | Phase II | |
| Land circulation | − 1.4642*** | − 0.0606 | ||
| 0.4682 | 0.1179 | |||
| Instrumental variables | 1.0036*** | 1.0036*** | ||
| 0.0254 | 0.0254 | |||
| Control variables | Yes | Yes | Yes | Yes |
| N | 3250 | 3250 | 3250 | 3250 |
Mechanism analysis
The previous section empirically tested the direct impact of land circulation on the physical and mental health of the elderly, and this section will focus on analyzing the mechanisms of the health impacts of land circulation. This study draws on the mediation effect test method (stepwise regression method) proposed by Baron and Kenny in 1986 to analyze the mechanism of internal and external effects on households. The stepwise regression method is logically intuitive and easy to understand and has been recognized and used by many scholars. The testing process is as follows. Firstly, the regression of land circulation on the mental health and physical health of the elderly is conducted. Secondly, the regression of land circulation on social interaction and average non-farm income of family members is carried out respectively. Lastly, there is a regression of land circulation and mechanism variables on the physical and mental health of the elderly.
The regression results of the mediated effect test are shown in Table 7. The first step of the stepwise regression method is the benchmark regression of this study. Therefore, the results will not be reported (reported in Table 2). At the same time, the existence of the main effect (significant regression coefficients of the benchmark regression) is a prerequisite for the existence of the mediating effect, and the impact of land circulation on the health of the elderly in the results of the benchmark regression does not pass the test of significance, indicating that it will not be analyzed for its mediating effect. Specifically, for external mechanisms, regression (1) shows that land circulation significantly increases the possibility of the elderly participating in social interactions, and regression (3) includes both land circulation and social interactions in the model, both of which have a significant negative impact on the mental health of the elderly. This suggests that the socialization effect of land circulation is one of the channels that affect the level of mental health of the elderly. For internal mechanisms, regression (2) demonstrates that land circulation significantly increases the non-farm income of elderly farmers, and regression (4) has a significant negative effect on the mental health of the elderly when both land circulation and non-farm income are included in the model. Through the mediating mechanism study, it is identified that social interactions of the elderly and the increase in non-farm income are important channels through which land circulation affects the mental health of the elderly.
Table 7.
Mediating effects of internal and external mechanisms within the family.
| Social interaction (1) |
Non − farm income (2) |
Mental health (3) |
Mental health (4) |
Physical health (5) |
Physical health (6) |
|
|---|---|---|---|---|---|---|
| Land circulation | 0.0325* | 0.7715*** | − 0.7180*** | − 0.4541* | − 0.0746 | − 0.0548 |
| (0.0193) | (0.0496) | (0.2002) | (0.2678) | (0.0585) | (0.0606) | |
| Social interaction | − 0.4994*** | − 0.1264*** | ||||
| (0.2476) | (0.0480) | |||||
| Non − farm income | − 0.2406*** | − 0.0616*** | ||||
| (0.0788) | (0.0202) | |||||
| Control variables | Yes | Yes | Yes | Yes | Yes | Yes |
| N | 3250 | 3250 | 3250 | 3250 | 3250 | 3250 |
Discussion
Under the background of the increasing aging in China, this study explores the impact of land circulation on the physical and mental health of the elderly and further explores the underlying mechanisms. Unlike previous studies, this research does not take health as one of the indicators for welfare measurement but examines the impact of land circulation and health separately. The results show that land circulation can significantly improve the mental health of the elderly, whilst the coefficient of influence on physical health is negative but not significant. The possible reason for this is that the physical health status of the elderly, as opposed to mental health, is the result of the accumulation of various factors over time, such as the economy, individual lifestyles, and habits2. It is difficult to capture changes in the physical health of the elderly using only one year of data, but the negative impact coefficient also implies the possibility of this potential outcome. Mazzonna and Peracchi used data from the Survey of Health Ageing and Retirement in Europe (SHARE) to examine the effects of retirement on health41. Their research showed that stopping work can enhance both physical and mental well-being, particularly for individuals in physically demanding jobs. Similar results were also found in studies conducted by Vo and Phu-Duyen42 and Abeliansky and Strulik43.In other words, continuing to work after retirement hurts the health of manual workers. Nishimura et al. replicated the study by replacing the data or research methodology, ultimately attributing the disparities in findings to the differences in the data and research methods used by the researchers44. However, it is still possible to distill a consensus from the literature across perspectives that the impact of retirement on health is correlated with the type of work an individual does and that for manual workers, stopping work enhances health. Agricultural production activities are physical labor and require a great deal of physical strength to continue at retirement age. If any one of these activities or the sum of the various activities exceeds the body’s tolerance limit, health is bound to be impaired by physical strain or overwork.
Further analysis reveals that older people who transfer their land are significantly better off than those who do not in terms of household non-farm income and socialization. Previous studies have found that both higher income and socialization activities are important factors affecting health in old age. Despite this, due to data limitations, it is barely possible to separate the non-farm income of older adults from the household level. The pattern of intergenerational family relationships in China is a “nurturing-supporting” feedback model, where generation A nurtures generation B and generation B supports generation A. Especially in rural areas, children’s support is the major means by which the elderly have access to resources for old age. Thus, higher incomes at the household level will indirectly improve the standard of living of older people and their access to health services.
Existing research has confirmed that land circulation is an essential way to achieve agricultural modernization45–47, and the Chinese government has introduced many policies to promote land circulation. Although a series of measures have promoted land circulation, the rate of land circulation in China is still low compared with developed countries. This is mainly due to the strong dependence of farmers on land48,49. China’s current social security system is mainly limited to urban areas, while social security in rural areas is relatively weak. The existing “New Rural Cooperative” and “New Rural Insurance” also have drawbacks such as low reimbursement and low levels of protection50,51. In this way, while providing resources for farmers, land has taken on an even more important social security function. At the present stage, the process of population aging in China is accelerating, with the degree and speed of aging in rural areas significantly higher than in urban areas. Engaging in agricultural production after reaching retirement age will intensify the physical burden on the elderly in rural areas and pose potential health risks. This is not only detrimental to the realization of a healthy China but also hinders the modernization of agriculture and rural areas. Therefore, improving the pension security system linked to land circulation and weakening the security role of land may become crucial directions for China’s land reform in the future.
The limitations of this study are as follows. Firstly, this paper utilizes survey data from the CHARLS study conducted in 2018. Although the endogeneity issue is addressed using the propensity score matching method, the challenge of omitted variable bias remains. Consequently, follow-up research can benefit from using tracking data to improve causal inferences. Secondly, due to the limitations of the questionnaire structure, we are unable to collect more detailed information on agricultural land circulations and household income. In the future, we will seek more refined data to validate our research findings further and supplement the mechanism of action. Thirdly, the physical and mental health of the elderly is a complex social phenomenon influenced by various factors. Although this paper presents a dual-system mediation framework examining both internal and external family mechanisms, it has primarily identified factors related to psychological health. However, the physical health of the elderly is also a significant social issue. Therefore, further research will focus on exploring the factors and mechanisms affecting the physical health of the elderly in greater detail, including aspects such as environmental factors and access to healthcare services. Fourthly, to further support the claim that “land circulation can improve the mental health of older people,” it is essential to include a wider variety of mental health assessment parameters in future studies, such as anxiety scales and stress scales.
Conclusions
Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) 2018, this research probed into the effect of land circulation on the physical health and mental health of the elderly and its underlying mechanisms. The main conclusions of this paper are as follows. First, land circulation has a positive effect on the health of the elderly in rural areas, improving their mental health. Second, the increase in non-farm income and the social interaction among the elderly are the main channels through which land circulation affects their mental health. Third, land circulation significantly enhances the physical health of the elderly (> 70 years old). Therefore, under the background of population aging and the comprehensive rural revitalization strategy, the Chinese government should actively encourage rural elderly people to participate in land circulation, continuously establish and improve the mechanism of land circulation for the rural elderly population, and reduce the elderly’s reliance on land for employment and old-age security functions. At the same time, we should also give full play to the synergistic effect of families and villages, organize activities for the elderly to strengthen emotional communication among them and help each other. Finally, the government should continuously promote the transfer of rural labor, fully tap the absorption capacity of rural labor in towns and counties, and encourage nearby employment opportunities for elderly family members, which not only ensures an increase in family members’ income levels but also enables effective care for the elderly at home.
Supplementary Information
Acknowledgements
The authors acknowledge the support of the CHARLS Program at Peking University (http://charls.pku.edu.cn/) for providing access to the data.
Author contributions
Conceptualization: Yuan Zhang, Shouhui Cao. Formal analysis: Yuan Zhang, Fei Sun, Lijun Wang. Methodology: Fei Sun, Shouhui Cao. Resources: Shouhui Cao, Fei Sun. Software: Yuan Zhang, Shouhui Cao. Writing—original draft: Yuan Zhang, Shouhui Cao. Writing—review & editing: Yuan Zhang, Fei Sun, Lijun Wang, Shouhui Cao.
Funding
This work was supported by the Research Startup Fund of Chaohu University (Grant No. KYQD-2025094).
Data availability
The data that support the findings of this study are available from CHARLS (http://charls.pku.edu.cn/) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of CHARLS.
Declarations
Competing interests
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Ethics approval and consent to participate
This study is a secondary analysis of the data from the CHARLS. The CHARLS study was approved by the Ethics Committee of Peking University (IRB00001052–13074). The participants provided their written informed consent to participate in this study. And informed consent was obtained from literate participants and legal guardian(s)/next of kin of illiterate participants. All methods were performed in accordance with the guidelines and regulations.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-025-02479-w.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available from CHARLS (http://charls.pku.edu.cn/) but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of CHARLS.