The interaction of social capital, life stress index and gender on mental health education for internal migrants: based on the China Migrant Population Dynamics Survey in 2017

Background: China has about 240 million internal migrants(IMs), and they face lots of mental health risks. The government is actively promoting mental health education for IMs. Previous studies have focused more on the relation between social capital and mental health, but ignored the impact of social capital on the accessibility to mental health services. Methods: Data from the China Migrant Dynamic Survey of 2017, involving 138939 IMs in 31 provinces were used to explore the interaction of social capital, life stress index and gender on acceptance of mental health education(AMHE). Social capital was divided into cognitive(CSC) and structural social capital (SSC). Multiple line charts and multi-level logistic regression were conducted to analyze their impacts on AMHE, and whether such impacts were moderated by gender and life stress index(LSI). Results: The results suggest: (1) The SSC ranking of IMs with different LSI levels was "moderate (3.62 ± 1.736), mild(3.53 ± 1.755), severe(3.53 ± 1.755)", SSC was positively correlated with AMHE(OR=1.320, 95%CI 1.305 to 1.336), but the correlation would decrease with the increase of LSI(OR=0.969, 95%CI 0.953 to 0.985; OR=0.949, 95%CI 0.934 to 0.964); (2) Males’ SSC(3.67 ± 1.780) was signicantly higher than that of females(3.36 ± 1.614), but its inuence on AMHE of females was higher(OR=1.050, 95%CI 1.036 to 1.064); (3) The CSC ranking of IMs with different LSI levels was "mild(3.71 ± 2.096), moderate(3.71 ± 2.076), severe(3.42 ± 2.024)", there was no signicant gender difference in CSC, and CSC was positively correlated with AMHE(OR=1.087, 95%CI 1.076 to 1.098), but gender and LSI had no signicant moderating


Background
Over the past three decades, social change has led to unprecedented massive internal migration in China. An increasing number of people leave their original places of residence to work and live in other provinces or cities to improve their lives, such people are called internal migrants(IMs). The number of IMs was more than 240 million in 2017 [1]. Epidemiological research has documented that migration contributes to the risks of mental illness [2], but internal migration is different from cross-border migration. Some surveys in China have pointed out that IMs could be vulnerable to discrimination and stigmatization, and also might become stressed by nding work, housing, schools for their children, and health care without the protections and bene ts [3]. IMs tend to show more symptoms of depression and anxiety and lower levels of mental health [4][5][6][7][8]. The high level of psychological distress suggests that efforts targeting mental health promotion and mental disorder prevention among the IMs are an urgent need.
Providing mental health education(MHE) is a good way to address this need. For the restrictions of systems, the IMs encounter obstacles in accessing local public health services(PBS), which has become an important risk affecting the health of the migrants [9], but the situation has been improving over the past decade. In 2009, China initiated the National Essential Public Health Services (NEPHS) project, it required local Community Health Centers to provide NEPHS to all residents in their area, including migrants who have lived there for more than six months [10]. The National Health Commission(NHC) reintroduced measures to promote the NEPHS equalization of IMs in 2013, and health education was one of the priorities, including MHE [11]. On the New Year's Day in 2016, China promulgated the Interim Regulations on Residence Permits, stipulating that migrants with residence permits enjoy the same treatment as local residents in receiving PBS [12]. In June 2016, NHC launched the Action Plan on Health Education and Promotion for the Migrant Population (2016-2020) to carry out extensive health education and promotion activities among the IMs [13]. The government's efforts have indeed contributed to a rapid rise in the proportion of migrants receiving health education [14]. However, the current data is still far from the national planning target, and the underlying reasons need to be revealed.
Studies have con rmed that gender, education, community type and migration range have signi cant impacts on the health education of IMs [15][16][17][18]. Although studies believe that social capital plays a prominent role in migrants' access to PBS [19,20], it is more often used to discuss its in uence on IMs' mental health [6][7][8][21][22][23][24] while ignoring its value in the process of access to PBS. However, access to health services has been suggested as a pathway by which social capital in uences health outcomes [25]. The study by Hou et al. [26] was an exception, they con rmed the positive effect of individual structural social capital on the health education of the IMs. From the social resource perspective, social capital can in uence the frequency of health information seeking and the diversity of used sources positively through three mechanisms: increased exposure to health information, enhanced seeking abilities, and reinforced health culture or norms embedded in social networks [27]. Guo et al. [28] have pointed out that the biggest obstacle for Chinese IMs to access services is the lack of information related to NEPHS. Therefore, it is possible that social capital plays an important role in the process of migrants' access to mental health services, but the relevant research is still lacking.
At present, many studies on the social capital of migrants are based on the background of developed countries. Due to the interdependence of cultural, economic, and social capital [29], the relationships between social capital and health are not consistent across countries [30]. Considering the characteristics of social capital of Chinese people [31,32], and the lack of social capital of IMs in the destination [33,34], it is necessary to re-examine the relationship between social capital and the accessibility of mental health services in the context of China. Reviewing the existing studies on social capital and PBS for the IMs in China, they are largely based on regional samples or early national samples, and therefore can not describe a recent national pro le. Moreover, there are at least three inadequacies: (1) Social capital can be divided into cognitive(CSC) and structural social capital(SSC), both CSC and SSC can independently in uence health outcomes [35], the in uence of SSC on the PBS for IMs has been studied [26], but the in uence of CSC has not been studied. (2) Research trends in social capital and health have moved towards the detailed analysis of the differences in this relationship among subgroups (e.g., gender) [36]. However, most of the studies in China have adopted the independent effect multi-factor model. This approach fails to provide evidence that the relationship between social capital and health is moderated by other variables. (3)Two models have been put forward by Cohen and Wills [37] to explain the mechanisms by which social relationships in uence health outcomes: the main effect model and the stress-buffering model, but few studies have considered both effects together.
In this study, we used a 2017 national IMs sample, taking acceptance of MHE(AMHE) as the outcome variable, introducing life stress index(LSI) and gender as moderators, and planned to respond to three questions: (1) what is the difference in the relationship between SSC and AMHE among people under different survival pressures? (2) will the relationship between SSC and AMHE be signi cantly moderated by gender? (3) will the situation be similar between CSC and SSC, or are there signi cant differences? Obviously, our ndings could help deepen the understanding of the relationship between social capital and access to PBS, and also provide a reference for the improvement of relevant policies of the Chinese government and other developing countries.

Data
The data was obtained from the China Migrant Dynamic Survey (CMDS) in 2017 and was provided by the Migrant Population Service Center. CMDS is an annual national sample survey of the internal migrants organized by the NHC from 2009, with an annual sample size of approximately 200,000 households. CMDS adopts the layered, multi-stage, and proportional to scale PPS (Probability proportional to size) sampling method. This study adopted the individual questionnaire A of CMDS, which was uniformly printed and distributed by the NHC. The questionnaire A includes basic information about respondent's demography, perception of the destination, the state of social interaction, and utilization status of NEPHS, etc. Full-time investigators collected the questionnaire data through household interviews, and each respondent gave informed consent before commencing the interview. Dates were entered through the migrant population health and family planning dynamic monitoring system, input data was subjected to multiple checks to ensure quality. The respondents consisted of internal migrants aged 15-59 living in the destination for more than one month. In this study, the inclusion conditions were set as "18-59 years of age, residence duration more than one year. Finally, 138939 people were included in this study. The mean age of the sample was (36.18 ± 9.271) years, and the mean residence duration was (7.21 ± 5.893) years.

Measurement
Dependent variables AMHE was set as a dependent variable, the question was: have you received MHE in your host community in the past year? Yes = 1 and no = 0.

Independent variables
Social capital was the independent variable of this study. It refers to the resources and bene ts received through connections with others, either as individuals or groups [35]. The concept can be broken down into two dimensions: SSC and CSC. SSC refers to the presence of formal opportunity structures or activities in which individuals build or strengthen their social connections. These structures and activities are often operationalized through measures of an individual's civic or social participation. CSC generally refers to individuals' perceptions, beliefs, and attitudes toward their social surroundings, with corresponding measures focused mainly on the concepts of generalized and particularized trust [38]. In this study, social capital was limited to the destination, and it was a localized social capital that re ects the social resources available to the migrant population there.
The SSC of this survey included civic participation and social participation in the destination. Questions of the former were: "since 2016, have you made suggestions to your unit/community/village or supervised the unit/community/village affairs management", "since 2016, have you participated in property donation, blood donation, volunteer activities, etc.", "since 2016, have you reported the situation/put forward policy suggestions to relevant government departments in various ways ", "since 2016, have you posted online comments on national affairs and social events or participated in related discussions", "since 2016, have you participated in party/youth league organization activities and party branch meetings". There were four-level answers for each question: 1= no, 2 = occasionally, 3 = sometimes, and 4 = often, the score ranged from 5 to 20. The question of social participation was "have you participated in any of the following activities in the past year: trade unions, volunteer associations, homecoming associations, fellow-students association, home town chamber of commerce, others", the score ranged from 0 to 7. According to the distribution characteristics of scores, civic participation was integrated into 5 levels: 1(5 points), 2(6 points), 3(7 points), 4(8 points), 5(9-20 points). Social participation was also integrated into 5 levels: 1(0 points), 2(1 points), 3(2 points), 4(3 points), 5(4-6 points). The spearman correlation coe cient of civic participation and social participation was 0.366 (p<0.001), and the SSC grade can be obtained by adding the two grades, and 7 grades were: 1(2 points), 2(3 points), 3(4 points), 4(5 points), 5(6 points), 6(7 points), 7(8-10 points).
The CSC generally referred to IMs' perceptions, beliefs, and attitudes toward their destination in this study, with corresponding measures focused mainly on the concepts particularized trust [37]. There were 5 questions in the survey: "I like the city/place I live now", "I am concerned about the changes in the city/place I live now", "I am very willing to blend with the local people and become a part of them", "I think the local people are willing to accept me as a part of them", "I feel locals look down on outsiders", each question was graded as "totally disagree", "disagree", "basically agree", or "totally agree", α=0.779. According to the distribution of scores, CSC was divided into 7 levels:1(5-14 points), 2(15 points), 3(16 points), 4(17 points), 5(18 points), 6(19 points), 7(20 points).

Moderating variables and controlling variables
LSI and gender were set as moderating variables. The question of LSI was "At present in the local area, does your family have the following di culties: nding a stable job, affording a house, schools for their children, the income is too low, life is not used to, and other di culties". These di culties are thought to be frequently dealt with by migrants [3]. According to the distribution characteristics of scores, LSI was integrated into 3 levels: mild(none), moderate(had 1-2 di culties), severe(had 3-6 di culties). Education, migratory range, and community type were set as the control variables. According to the compulsory education years in China, education was divided into two categories: ≤9 and >9 years groups, and the community types were divided into urban and rural areas, the migratory range was divided into inter-province and intraprovince.
Statistical analysis SPSS 22.0 was used for data analysis. Firstly, we present the descriptive statistical data in order to describe the general characteristics of the included sample. Secondly, we used univariate analysis, AMHE was taken as the dependent variable and other included factors were taken as independent variables for cross-table analysis to investigate whether each factor had a signi cant impact on the dependent variable, the test index was the chi-square value. Thirdly, we compared differences in CSC and SSC among subgroups of gender and LSI with independent sample t-test and one-way analysis of variance. Fourthly, we used multiple line charts to explore the in uence of interaction effects among gender, LSI, CSC and SSC on AMHE. Finally, a hierarchical logistic regression analysis was conducted with AMHE as the dependent variable, CSC, SSC as the independent variables, gender and LSI as the moderating variables, and education, community type and migratory range as the control variables, the aim is to investigate the moderating effects of LSI and gender on the relationship between social capital and AMHE.

Characteristics of the sample
The data in Table 1 shows: about 35.9% of the IMs received MHE in the community in the past year, which was a relatively low number; the sample had a similar ratio of male to female (51.4% VS 48.6%), nearly three quarters (74.2%) of the population lived in urban communities, and the number of inter-provincial migrant population was slightly less than that of intra-provincial migrant population (48.8% VS 51.2%); the migrant population did have higher LSI, with the proportion of mild, moderate and severe groups being 43.3%, 25.8% and 30.9%, and more than half of the IMs would face at least one life di culty; the social capital of the IMs was characterized by high CSC and low SSC, the proportion of CSC in the low group (5-14 points) was only 15.7%, while that in the high group (≥16 points) was 57.2%, the proportion of SSC in low subgroup(2 points) reached 38.4%, this means that more than one third of the migrant population had neither civic nor social participation in the past year.  Table 2 showed that: the gender difference of AMHE was not signi cant, while the proportion of AMHE was higher for people with higher education years, living in urban communities and migration within a province. The correlation between LSI and AMHE was non-linear, people without life hardship being listed in the study had a higher AMHE. Among people with living di culties, the AMHE increased with the increase of LSI. The impact of social capital on AMHE was very prominent, higher CSC corresponds to higher AMHE, the same was true of the SSC, and the impact of SSC on AMHE was signi cantly greater than that of CSC. Note: ***p<0.001, **p<0.01 *p<0.05. The same is true of the symbols in the rest of the table.
Impact of gender and LSI on CSC and SSC In Table 3, independent sample t-test showed that there was no signi cant difference in CSC between males and females, but SSC of males was signi cantly higher than that of females. One-way ANOVA found signi cant differences in CSC and SSC among the three groups of LSI. The Bonferoni method was used for post comparison, and the following results were obtained: the CSC of group mild was not signi cantly different from that of group moderate, and both groups were signi cantly lower than that of group severe; the ranking of SSC of group moderate was signi cantly greater than that of group mild, which in turn was signi cantly greater than that of group severe.
Interaction of gender, LSI,CSC, and SSC on AMHE Firstly, the interaction of gender, CSC and SSC on AMHE was explored. As shown in Figure 1, with the improvement of CSC, we could see that the AMHE curves of both males and females were slowly rising, and the distance between the two curves was very close, indicating that the interaction effect between gender and CSC might not be signi cant. In Figure 2, with the improvement of SSC, the AMHE curves of both males and females also rose slowly, but the curves of females always stayed at the top and the distance between the two curves gradually widened, indicating that the interaction between gender and SSC might be signi cant, and SSC of females would have a greater in uence.
Then, we explore the interaction of LSI, CSC and SSC on AMHE. In Figure 3, with the increase of CSC, all three groups of curves showed an upward trend. The curve of group mild always stays at the top, followed by group severe and moderate.
The trend of the three curves was nearly parallel, indicating that the interaction effect between LSI and CSC might not be signi cant. In Figure 4, with the improvement of SSC, all three groups of curves also showed an upward trend. However, the distance between group mild and severe showed an increasing trend, while the distance between group severe and moderate showed a decreasing trend, indicating that interaction effect between LSI and SSC might exist.

Results of multivariate analysis
In , it could be found that after controlling other variables and interaction effects, the main effects of gender and LSI were signi cant, AMHE of males was signi cantly higher than that of females, AMHE of group severe was signi cantly lower than that of group mild, but there was no signi cant difference between group moderate and group mild. The main effects of CSC and SSC were also signi cant, and AMHE increased with the increase of CSC(or SSC). It should be pointed out that the interaction effect of CSC with gender and LSI was not signi cant, while the interaction effect of SSC with gender and LSI was signi cant. The OR value of Gender*SSC was signi cantly greater than 1, and those of Moderate*SSC and Severe*CSC were signi cantly less than 1. In addition, we did not nd that the OR value of Gender*SSC*LSI was signi cant, so it was not presented in table 4.

Discussion
There were three main ndings in this study: (1) The SSC ranking of IMs with different LSI levels was "moderate, mild, severe", SSC was positively correlated with AMHE, but the correlation would decrease with the increase of LSI; (2) The SSC of males was signi cantly higher than that of females, but the in uence of SSC on AMHE of females was more prominent; (3) The CSC ranking of IMs with different LSI levels was "mild, moderate, severe", there was no signi cant gender difference in CSC, and CSC was positively correlated with AMHE, but gender and LSI had no signi cant moderating effect on it.
Migration means a loss of the original social network and a disruption in civic participation in the new environment, particularly if migrants view the move as temporary and have little stake or familiarity in the destination community, which results in the de ciency of the migrants [39]. Previous studies have pointed out that the social participation of the Chinese migrant population is insu cient and the members of social networks tend to be in the middle and lower classes [33,34].
The study found that the SSC of the IMs was indeed insu cient, 38.4% of whom had neither civic participation nor social participation in the past year. LSI and SSC were closely correlated, but the correlation was not linear. The SSC of the moderate group is the highest, followed by the mild group, and the group severe was signi cantly reduced. These ndings are important supplements to the de ciencies of the existing studies. We also found that the SSC of males was signi cantly higher than that of females, which may be related to the content included in this study. The included options are more external to the family, while compared with males, females' social relations are more inclined to family and relatives [38].
Although the SSC of the IMs is insu cient, it can effectively promote the AMHE by the migrant population in the community. With the restriction of other variables, the AMHE could increase by about 32.0% for each increase of SSC unit, this is consistent with some studies [26,27,40]. According to Song et al. [27], SSC could increase exposure to MHE information for IMs, enhance their seeking abilities of MHE, and reinforce mental health culture or norms embedded in social networks. This study found that SSC had different effects on AMHE under different life stress situations. Although SSC was not the highest in the mild group, its in uence on AMHE was the strongest; while the SSC was the highest in the moderate group, its in uence on AMHE was weakened; and both the SSC and its in uence on AMHE were the lowest in the severe group. The Network-Episode Model [41] believes that the supporting role of social relations not only depends on its scale, but also depends on its density, durability, reciprocity and other structural characteristics. Previous studies have con rmed that structural differences in social networks can indeed affect health information seeking behavior [27]. Clearly, the SSC of the group moderate had quantity, but lacked quality, while the group severe lacked both. Gendered social roles and norms may act at multiple levels to shape the structure and composition of men's and women's social networks and, by extension, the types of resources that they have access to in their networks [38]. Therefore, the impact of social capital on health is different between genders. Landstedt et al. 's study [42] found that SSC has a greater impact on health of men, while Moore and Carpiano [38] emphasized that social capital seemed more salient for women's health. This study also found this difference, although the SSC of females was lower, its impact on AMHE was greater than that of males, it con rmed Moore and Carpiano's points.
In this study, the CSC of the IMs showed a relatively high level. 93.3% of the IMs think that the local people accept them, and only 17.1% feel the discrimination of the local people, two gures were signi cant improvements over the data(74.3% and 25.7%) obtained in a 2008 regional survey by Ren and Tao [43]. Whether this is due to sample differences or changes in the overall social environment remains to be con rmed. CSC is signi cantly positively correlated with AMHE, indicating that the more positive the evaluation of the destination is, the more likely it is to encourage the IMs to seek local mental health services. But the impact of CSC was signi cantly lower than that of SSC. As proposed by Guo et al. [28], the biggest obstacle for the IMs to access NEPHS is the lack of information, the informational capabilities contained in SSC may make it more valuable for the IMs to obtain MHE. Unlike SSC, the impact of CSC on AMHE was not moderated by LSI and gender. Given the high level of CSC, this may have created a ceiling effect, resulting in CSC differences between gender(or LSI) subgroups not being su cient to generate signi cant AMHE differences. It is quite different from some studies based on western cultural background [38]. More cross-cultural studies are needed to esh out these ndings.
Kawachi and Berkman [25], when talking about the relationship between social ties and mental health, pointed out: the stress-buffering model posits that social ties are related to well-being only for persons under stress, whereas the main effects model proposes that social ties have a bene cial effect regardless of whether individuals are under stress. It has been suggested that structural aspects of social relationships (e.g., social networks, social integration) may operate via main effects, whereas functional aspects of social relationships (e.g., perceived support) operate through a stressbuffering mechanism. In this study, the analysis results showed that SSC had both a main effect and a buffering effect, while CSC only showed a main effect. This is the rst time such a phenomenon has been found in the migrant population, our choice of outcome variables may be a reason, but further research is needed to con rm and explain it.
Two things have to be pointed out. First of all, the selection of SSC measurement content in this study has strong Chinese cultural characteristics, such as homecoming associations, Party branch of the Chinese Communist Party and Communist Youth League, etc., which is di cult to nd counterparts in the research based on other cultures, which may affect the comparability of different research conclusions to a certain extent. Secondly, our research limits the acceptance scope of MHE to the community. In China, the community usually refers to the village committee or street, which is different from the concept of community in western culture, and its scope is smaller. Such a setting may may reduce the function of social capital. After all, the geographical background of social capital is the whole city in this study.

Conclusions
The social capital of Chinese IMs was characterized by high CSC and low SSC, and the in uence of SSC on AMHE was signi cantly greater than that of CSC. The correlation between LSI and social capital of IMs was non-linear, and LSI could weaken the in uence of SSC on AMHE. Gender difference only exists in the SSC. Although the SSC level of males was higher than that of females, the in uence of SSC on AMHE of females was stronger. In summery, SSC had both a main effect and a buffering effect, while CSC only showed a main effect. These ndings expanded our understanding of the relationship between social capital and mental health services among IMs. When promoting the mental health education of the IMs, the government should pay attention to enhancing their positive identity to the city and at the same time improve their civic participation and social participation.