The Effect of Labor Participation on The Health of Middle-Aged People——An Empirical Analysis From China

Background: China has entered into an aging society and will continue to age rapidly in the future. The middle-aged (45~59 years old) is aging, and the workforce participating in labor is shrinking. Since there is few empirical researches on the relationship between labor participation and the health of middle-aged people, the aim of this study is to study the effect of labor participation on the health of middle-aged people. Methods: The data of CHARLS in 2015 were adopted. In this study, self-assessed health, chronic diseases and depression were used as health measurement indicators, and the work status was used to measure the labor participation. To control possible endogenousness, our study used Propensity Score Matching to match people who participated in labor and those who did not; Then logit regression analysis was used among matched data to study the association of labor participation with the health of middle-aged people. Results: The study showed that the self-rated health of middle-aged people with labor participation was 1.3 times higher than those without labor participation. In terms of the probability of suffering from chronic diseases, middle-aged people who participated in labor were 0.6 lower than those who did not participate in labor. In terms of the probability of depression, the middle-aged people who participated in labor were 0.8 times lower than those who did not participate in labor. Conclusions: The health of middle-aged people participating in labor was obviously better than those who did not participate in labor. Our study provided the evidence for policy making on health promotion, delayed retirement and employment promotion.

the impact of residents' health on labor participation was essential [32]. Wei et al. (2013) found that from low-age group or high-age group, the health status signi cantly affected non-agricultural employment participation [33]. Li et al. (2014) found that hypertension had a signi cant effect on the labor participation of middle-aged and elderly in urban, but it had no signi cant effect on rural residents. Urban residents engaged in manual labor had higher requirements for physical health, and if they got sick, they would leave the labor market [34]. Wang et al. (2016) found that improving healthy human capital was conducive to promoting rural residents' labor participation, as well as increasing their agricultural labor time and raising their agricultural labor income. Labor income had no obvious impact on rural residents' labor participation, and the decline in long-term health status had a greater impact on rural residents' labor participation than short-term health shocks [35]. Liu et al. (2012) found that residents' labor participation increased signi cantly with the improvement of health conditions, [36]. Zhu et al. (2019) analyzed the impact of health on labor supply, and the results showed that the overall health status had a signi cant impact on the labor supply of the elderly [37].
Researchers mainly focused on the impact of health on labor participation, while the impact of labor participation on health is still in its infancy. At the same time, few studies focused on the effect of labor participation on the health of middle-aged people. This study investigates whether labor participation signi cantly affects the health of middle-aged people. Based on the conclusions about the relationship between health and labor participation in previous studies, we propose the following research hypotheses: Hypothesis 1: Labor participation has a positive effect on the SAH of middle-aged people.
Hypothesis 2: Labor participation has a positive effect on the chronic diseases of middle-aged people.
Hypothesis 3: Labor participation has a positive effect on the depression of middle-aged people.

Data
In this study, we used the 2015 CHARLS data. CHARLS is a set of high-quality micro-data representing households and individuals aged 45  Our study focused on the middle-aged people. According to the WHO's division on age, we de ned that the middle-aged people were those of 45~59 years old [39].

Health Status Measurement
SAH is an indicator used to re ect health status. The CHARLS questionnaire set up two surveys on SAH. Each survey set questions on SAH twice. The rst was at the beginning of the survey and the second was at the end of the health survey. The respondent may not be very familiar with the survey at the beginning of and the corresponding scores ware: 1 point, 2 points, 3 points, 4 points. The positive statements were just the opposite. The corresponding scores were: 4 points, 3 points, 2 points, 1 point, respectively. The score range of CES-D10 was from 0 to 40. The lower score meant lower depression. 0~20 points indicated no depression, 21~40 points indicated suffering from depression [41]. We de ned depression as 1 and no depression as 0.

Variables
Considering the previous study, we used socioeconomic status, demographic characteristics and living environment as core explanatory variables and control variables[42~44].

Independent Variables
The core explanatory variable of this study is labor participation. In the CHARLS questionnaire, the respondent was asked whether he/she had engaged in agricultural production or business activities for more than 10 days in the past year. If the respondent replied less than 10 days, the respondent would be asked whether he worked more than one hour last week. The work status included employment or self-employment, such as civil servants, enterprise employees, self-employment, and help for their own companies without remuneration; while domestic work and volunteer services were excluded. If the respondent replied that he/she wasn't engaged in farming and other work, he/she would be asked whether he/she temporarily stopped working because of temporary leave, sick leave, or receiving on-the-job training. Then the respondent would be asked whether it was more than 6 months. When he/she can return to his/her original job position, he/she also was de ned that he currently had a job. In the CHARLS questionnaire, the measurement of this variable was obtained by comprehensive calculation of the following four questions: Question 1: Did you engage in agricultural work (including farming, forestry, shing, and husbandry for your own family or others) for more than 10 days in the past year?
Yes No Question 2: Did you work for at least one hour last week? We consider any of the following activities to be work: earn a wage, run your own business and unpaid family business work, et.al. Work does not include doing your own housework or doing activities without pay, such as voluntary work. 1.Yes

2.No
Question 3: Do you have a job but are temporarily laid-off, or on sick or other leave, or in-job training? 1.Yes

2.No
Question 4: Do you expect to go back to this job at a de nite time in the future or within 6 months? 1.Yes

2.No
According to International Labor Organization (2013) [45], we de ne the following three types as not participating in labor: (1) not engaged in the past year agricultural production and operation activities; (2) be engaged in other work for less than 1 hour per week; (3) be engaged in temporarily stopped working for various reasons, at the same time, there is no certainty that they will return to their original jobs within six months. We de ne the participation of labor in the state of work with the exception of the three types.

Control Variables
Previous studies showed that economic resources had a positive impact on health [46]. Only with a certain economic strength is it possible to participate in health clubs, obtain adjuvant treatment for quitting smoking and drinking and so on. [47]. Based on previous researches, our study selected individual demographic characteristics (gender, age, marriage and education), social activities, drinking, smoking, health before the age of 15 and family property as control variables. The de nition and measurement of speci c variables are shown in Table 1.

Propensity Score Matching Method
The labor participation of middle-aged people may be affected by health factors, some unobserved factors of their own, endogeneity and so on. As the regression model using cross-sectional data may cause data bias and confounding variables, Propensity Score Matching (PSM) was used to match those who participated in labor and those who did not. PSM is aimed to reduce the in uence of these biases and confounding variables in our study. In order to explore the relationship between a certain factor (exposure or intervention, hereinafter collectively referred to as treatment factor) and health outcome, we should build a control group for comparison. The purpose of our study is to control the interference of non-treatment factors and highlight the effect of treatment factors (Average Treatment effect on the Treated, ATT). The calculation formula of ATT is as follows: hi1 and hi0 indicate the health status of those who participated in labor and those who did not. The logit model is generally used to estimate the probability of whether the respondents enter the treatment group, that is, the probability of middle-aged labor participation. The propensity score estimation model is as follows: PSM includes nearest neighbor matching, radius matching, kernel matching, local linear regression matching, and spline matching. We used three methods of radius matching method, caliper matching method and kernel matching method to match in our study, mainly focusing on the nearest neighbor matching method. The nearest neighbor matching method refers to setting a radius r in advance. If the radius value is smaller, the matching number is fewer .

Logistic Regression
Logistic regression deals with bivariate dependent variables or multivariate variables. In our study, the dependent variable is a 0-1 binary variable. In order to explore the effect of labor participation on the health of middle-aged people, we combined with the regression equation of health and health level proposed by Wagstaff (2003), and we set the logit model as follows: h is a binary variable that represents the health status of individual; i. represents SAH, chronic diseases and depression. Work status represents labor participation and it is the core explanatory variable in this study. x is the control variable, including gender, age, educational status, etc.

Statistical Analysis
We de ned the middle-aged people who don't participate in labor as a control group (no labor participation = 0), and the middle-aged people who participate in labor as a treatment group (participation labor = 1). Then we matched the two groups to improve the comparability. The descriptive statistics of the variables are shown in Table 2. 4.40% in control group and 24.49% in treatment group of middle-aged people reported that they were healthy. 80.84% of the middle-aged people participated in work, and 19.16% of middle-aged people did not participate in work.

PSM analysis results
In lines with Aladie et al (2004), the Mean Square Error (MSE) can be minimized under normal circumstances in one-to-four matching [48]. We used nearest neighbor matching within caliper with k=4 for one-to-four matching estimation, to perform replacement matching and allow ties. Among a total of 4418 observations, 3 observations in the control group (Untreated) were not in the common value range, 920 observations were in the value range, and 7 observations in the treatment group (Treated) were not included. In the value range, 3488 observations were in the value range. Table 3 showed the matching result. It can be seen that the standardized deviations (% bias) of all variables after matching were mostly less than 10%. From the results of t test before matching, gender, age squared/100, education status, marital status, middle, urban and rural, drinking, smoking variables were statistically signi cant. After matching, the differences of the four variables of gender, educational status, social activities, and drinking disappeared signi cantly. It showed that PSM signi cantly alleviated the self-selection problem. In addition, after matching, the standardized deviations of all variables were greatly reduced.
As Table 4 shows, after matching, the estimated value of ATT is 0.08, and the corresponding t value is 3.70( >1.96), which is statistically signi cant. We also used the nearest neighbor matching method, caliper matching method and nuclear matching method to conclude the matching. Table 4 shows the matching results, and the results of the three matching methods all showed that labor participation had a signi cant impact on the health of middle-aged people. And the matching results were very similar, indicating that the matching results were robust.

Regression statistical results
We used the matched data for logit regression analysis to analyze the association between labor participation and the health of middle-aged people. We showed the normal standard errors and robust standard errors in Table 5.
From the model 1 in Table 5, the SAH of middle-aged people with labor participation was 1.3 times higher than those without labor participation. In terms of the probability of suffering from chronic diseases, middle-aged people who participated in labor were 0.67 lower than those who did not participate in labor; and in terms of the probability of depression, the middle-aged people who participated in labor were 0.84 times lower than those who did not participate in labor. From the results of Model 2-3 in Table 5, the SAH and chronic diseases of middle-aged people in urban and rural areas were statistically signi cant, but depression was not statistically signi cant. According to the results of age-based models 4-6, the SAH, chronic disease and depression in 45-49 years old and 50~54 years old were not statistically signi cant, while the 55~59 years group was statistically signi cant.
Compared to most researchers focused on the labor participation and health of the elderly group, this study focuses on the effect of labor participation on the health of middle-aged people, because this group is more susceptible to policies such as delay retirement.
Our research shows that the health of middle-aged people participating in labor was better than those without participating in labor. Labor participation is the main means for middle-aged people to earn income and increase social communication activities, therefore, it is less likely for them to suffer psychological problems and depression compared to unemployment. It was in lined with the conclusions of Zhang et al.(2017) [49]. The aging society has prompted people to focus more on the health and health policies of the elderly, but ignores the policies of the middle-aged. Based on it, this article is a supplementary study of the relationship between labor participation and health. Our study found that labor participation had a signi cant impact on the health of middle-aged people. Middle-aged people are a potential group that will develop to the elderly people, and the total supply of labor in an aging society would be relatively reduced. From this perspective, public policies should be paid more attention to the employment security and health promotion of middle-aged people.
Researchers often explored the relationship between labor participation and health of the middle-aged and elderly people. Our study focused on middle-aged and highlighted the middle-aged group. Previous studies focused on the impact of health on labor participation, and this study supplements the impact of labor participation on health, which is also one of the innovations in this article. This article used PSM for matching analysis and then made a logit regression analysis using the matched data, which strongly supported the important discovery that labor participation promoted the health of middle-aged people. The results validated Hypothesis 1, Hypothesis 2 and Hypothesis 3. We found that the regression results were relatively close.
At the same time, we also found that in the age-group model, labor participation in the 55 ~ 59 age group had a signi cant positive effect on the self-rated health, chronic diseases and depression of middle-aged people, but between 45 ~ 49 years old and 50 ~ 54 years old was no statistical signi cance. The result showed that age was an important factor. Growing old made the positive effect of labor participation more obvious. It also showed that the appropriate delay in retirement age was bene cial to the health of the elderly. It was consistent with the conclusion drawn by Dong et al. (2016) that retirement had a negative impact on SAH and depression, and it had a more signi cant impact on women, lower education levels, and people aged 45 ~ 54 [50]. It was also consistent with the ndings of Lei et al.(2010) [51]. Researchers in developed countries had also conducted a lot of researches on the relationship between retirement and health. Early research found that retirement was not conducive to individual health, and Hurd's research in the United States found that individual's health status deteriorated after retirement [52]. Most western countries put forward an initiative on the retirement age. European countries have delayed their retirement ages since 2000. Taking Germany as an example, starting from January 2012, the legal retirement age of Germans has gradually delayed from 65 to 67. Before 2030, the 67-year-old retirement system will be fully implemented [53]. It shows that labor is an important requirement for health. Grip et al.(2012) also found that retirement reduced the contact between individuals and society, and the resulting depression is not conducive to physical health [54]. Mein et al. (2003) found that for most people, work and work-related activities may be the main daily physical activities, and nearly one-third of individuals would not participate in physical exercise after work [55]. Moderate exercise can reduce the incidence of chronic diseases such as coronary heart disease, diabetes, hypertension, and even alleviate psychological anxiety. If retirement reduces work as well as related physical activity, then retirement is not conducive to individual health. From the result of empirical research on the impact of social activities on health, foreign studies have shown that participation in various social activities can improve the life satisfaction and elderly' well-being, especially reducing depression and loneliness. Research on the effect of labor participation on health is directly related to the determination of retirement age. Unlike many developed countries implemented a exible retirement system, China implemented a mandatory retirement system[56-57], which may not be appropriate. We suggest that a exible retirement age policy can be formulated based on job characteristics and individual's need in China. At present, many studies have con rmed that it is feasible to delay the retirement age appropriately. For example, Tan et al. (2016) found that the healthy working ages in China were close to 62 and 58 years old in 2005 and 2010, respectively, which indicated that it would be feasible to delay the retirement age appropriately in China[58].
At the same time, middle-aged people in late-career should be properly protected. Once middle-aged people are unemployed, it is more di cult to return to work for them, and unemployment will cause economic and psychological problems for them. For instance, Maren et al. (2018) concluded that older employees who had returned to work after experiencing a late career had di culties in new work. Middle-aged people would lose income after they lost their jobs. What is worse, it was di cult to reach the original level of income after reworking. Getting new job skills and other obstacles would have a negative impact on the mental health of the elderly after unemployment [59]. The unemployment of middle-aged people is an important social problem faced by China, and the other countries. The British government has launched the "50-year-old new policy" plan aimed at reducing the unemployment rate of middle-aged people and promoting the re-employment of middle-aged unemployed people since 1999. Good economic and social bene ts have been achieved, which also provided important references for China to explore and solve related problems [60].
In this article, we used SAH, chronic diseases and depression as indicators of health measurement to comprehensively re ect the individual's perception of their own health. However, only the three indicators may not fully re ect health, which is a limitation of this article. Regarding the measurement indexes of health, BMI, actual blood pressure value, actual blood glucose value and other objective indexes re ecting physiological health could be introduced in the future.

Conclusions
This study focused on middle-aged people in China, and showed that the labor supply of middle-aged people had not been completely released. The health in SAH, chronic diseases and depression of middle-aged people participating in labor was obviously better than those who did not participate in labor. The nding may help provide evidences for social policies and intervention strategies in health promotion and employment promotion in an aging society. At the same time, the study also provided reference for relevant researches on labor participation and health.        Note: * p < 0.05, ** p < 0.01, *** p < 0.001; in order to conduct a robustness test, we made regression analysis on urban and rural areas, age groups, and region