Migration and Changing Family Relations in Rural China

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Inquiry Commodity

Rural-to-urban migration, bigotry experience, and wellness in China: Show from propensity score assay

• Yik Wa Law

Rural-to-urban migration, bigotry experience, and health in China: Show from propensity score analysis

• Zihong Deng,
• Yik Wa Constabulary

x

• Published: Dec 28, 2020
• https://doi.org/10.1371/journal.pone.0244441

Figures

Abstract

This research examines how rural-to-urban migration influences health through discrimination experience in China afterwards considering migration selection bias. Nosotros conducted propensity score matching (PSM) to obtain a matched group of rural residents and rural-to-urban migrants with a like probability of migrating from rural to urban areas using data from the 2014 Cathay Family Panel Studies (CFPS). Regression and mediation analyses were performed afterwards PSM. The results of regression assay later on PSM indicated that rural-to-urban migrants reported more discrimination experience than rural residents, and those of arbitration analysis revealed discrimination experience to exert negative indirect effects on the associations between rural-to-urban migration and three measures of health: self-reported health, psychological distress, and physical discomfort. Sensitivity analysis using different calipers yielded similar results. Relevant policies and practices are required to respond to the unfair treatment and discrimination experienced by this migrant population.

Citation: Deng Z, Law YW (2020) Rural-to-urban migration, discrimination experience, and health in Mainland china: Evidence from propensity score analysis. PLoS One 15(12): e0244441. https://doi.org/10.1371/journal.pone.0244441

Editor: Young Dae Kwon, Catholic Academy of Korea College of Medicine, South korea

Received: June 10, 2020; Accepted: December 9, 2020; Published: Dec 28, 2020

Copyright: © 2020 Deng, Law. This is an open admission commodity distributed nether the terms of the Creative Commons Attribution License, which permits unrestricted apply, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Data files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exists.

Introduction

Given the large calibration of and rapid increase in migration worldwide in recent years, the written report of the relationship among migration, discrimination, and health is highly pertinent to promoting migrant well-being. China, in detail, has experienced unprecedented internal migration, with the number of migrants, most of them rural-to-urban migrants, increasing from 6.57 one thousand thousand in 1982 to 221.43 million in 2010, with the annual increment rate of around ten% from 2005 to 2010 [1]. Data released by the National Bureau of Statistics (2012–2019) show, all the same, that the growth in the migrant population slowed from 2010 to 2014, and, since 2015, the size of that population has actually decreased [2]. Migrants in China are confronted with many difficulties, not least discrimination and health bug, with enquiry revealing greater health depletion the longer migrants remain in the migration destination [3, 4]. The extant literature also shows discrimination experience to exist associated with poorer wellness, including self-rated physical health and depressive distress [5, 6], which may help to explain the health disparities betwixt migrants and non-migrants. The influence of discrimination feel on health has been studied in a large torso of literature focusing on international migrants and racial/ethnic minority groups, and some studies in China have besides examined how discrimination influences health among migrants [five, 7], just the function of such experience in the human relationship between rural-to-urban migration and health in People's republic of china remains unclear. Indeed, rural-to-urban migrants in China are probable to have considerable exposure to unfair treatment and discrimination, in part considering of the rural-urban gap and various institutional barriers during the migration procedure [viii, 9]. Therefore, it is of interest to examine how rural-to-urban migration influences discrimination experience and further influences health outcomes. In addition, rural-to-urban migrants are a self-selected group, with some individuals more likely than others to drift from rural to urban areas. The factors affecting the migration decision may further influence post-migration discrimination experience and health, and information technology is thus necessary to address the aforementioned self-choice bias before conducting farther analysis.

Migration and health status

Migration is considered to exist an important factor influencing wellness outcomes. The relationship between migration and health is complicated through the firsthand and offsetting pathways, with some factors harmful and others beneficial for wellness, including both physical health and mental health [ten, 11]. The extant literature reports mixed results of wellness differences between migrants and non-migrants. A group of studies reveals that migration is positively associated with health, or the association between migration and health is not significant. The positive effect of migration on health is commonly related to the increase of income later on migration and better health services and resources in the migration destination. Researchers found that later decision-making the factors that affect the migration determination and health consequences in propensity score matching (PSM), short-term migration positively influence self-reported health. They too documented a close to zero affect of long-term migration on self-reported wellness in a panel dataset in Prc using rural non-migrants as the comparison group [12]. In terms of mental health, rural-to-urban migrant workers do non constitute a more vulnerable group than rural or urban residents, possibly due to the facts that the higher economic status and life opportunities that most migrants bask may lead to better mental wellness [13]. Zhang et al. [fourteen] too revealed that migration status was not significantly associated with psychological health using nationally representative information in China [fourteen].

It has been argued that migration can be a stressful state of affairs during which migrants' health may deteriorate over fourth dimension in the destination areas. In Red china, rural-to-urban migrants reported suffering a worse mental health status than both urban residents in immigrant communities and their rural counterparts in emigrating communities [15]. A literature review summarizes that major depression, depressive symptoms, and indisposition are the most common psychological outcomes amidst Chinese migrants and their families [16]. Migration and its related factors, such equally subjective and objective socioeconomic status, social support, adaptation and difficulties adjusting to a new surroundings, elapsing of migrant status, and social stigma, are associated with poor mental health [17, eighteen].

With respect to physical wellness, rural-to-urban migration is considered to be the main demographic factor driving the cardiovascular disease epidemic in Cathay [19], and data from other countries too support the link between such migration and such cardiovascular risk factors equally obesity, hypertension, and diabetes, with the affect of these risk factors associated with the age at which migration occurs [twenty–22]. Among female migrant workers in China, the longer the period of migration, the greater the hypertension risk [23]. However, one study also reported that migrants enjoyed significantly better concrete wellness than rural residents simply not urban dwellers [14]. The choice of the reference grouping for comparison conspicuously showed that migrants' physical health outcomes were not necessarily poorer than their hometown counterparts.

Given the inconclusive results obtained for health and mental health outcomes between migrants and non-migrants, it is necessary to examine the nature of the association between migration and different types of wellness-related outcomes in a large-scale dataset. Various socioeconomic, psychosocial, and behavioral factors may mediate the effects of migration on health, including economical status, living standards, physical conditions, level of social support, data on and admission to local health services, health-related investment, and lifestyle, etc. [x]. Although the existing studies take examined how the experience of discrimination influences wellness amidst migrants [5, 24], they pay less attention to whether migration makes individuals have more than exposure to discrimination and then further influences their wellness. The "wellness depletion effect" proposes that migrants' health deteriorates the longer they stay in the migration destination such that whatever health advantage migrants enjoy in the early stage of migration tends to diminish over time [3, 4]. A literature review have summarized that information technology is of import to examine the affect of social, economic, environmental, emotional, and behavioral gamble factors on migrants' health in futurity inquiry [sixteen]. From the perspective of the health depletion event, compared with other factors, bigotry experience could be one of the covariates that contribute to the negative clan between migration and wellness. Yet, the nature of such an association is unclear. Discrimination experience oftentimes defined by how rural-to-urban migrants perceive unfair encounters and how they sympathize their feel in the context of social inequality and rural-urban disparities. And the structural factors, such equally the household registration (hukou in Chinese) system and the conflict between individuals and governmental agencies, may help to elucidate the health depletion effect of migration in China.

Migration and discrimination

Rural-to-urban migration in China is closely related to the country's hukou system. The two master hukou types are agricultural and non-agricultural hukou. The system is highly selective, and information technology is very difficult to transfer one'southward hukou condition from agricultural hukou to non-agricultural hukou [8, 25]. Urban residents enjoy better public welfare and more than social services, such as the public provision of schooling, healthcare, housing, and retirement benefits, relative to rural residents [25, 26]. In improver to hukou type, hukou location (hukou suozaidi in Chinese) also matters. The provision of public welfare and social services is based on hukou location, and local governments tend to lack incentives to provide services for migrants given that fiscal decentralization has made room for the exercise of a discretionary power [27, 28]. Rural-to-urban migrants agree agricultural, non-local hukou, which means they have restricted admission to public welfare and social services in urban China. There has been recent hukou reform aimed at establishing a unified residential hukou without specifying the agricultural or not-agricultural blazon [29], but the welfare and social service reforms take not kept pace with the hukou reform. Accordingly, rural-to-urban migrants still do not take equal access to public welfare and social services. Indeed, such migrants are frequently treated equally second-class citizens, occupy marginalized positions, and face a multifariousness of institutional, economic, cultural, and social barriers in urban China [8, 9]. Apart from hukou-related bigotry, people have besides faced other social discrimination. Based on the data from the Mainland china Labor Dynamics Survey (2012), one written report revealed that electric current migrants were the least probable to perceive the fairness of electric current living standards compared with their efforts, while rural non-migrants were most likely to perceive the fairness of current living standard [30]. The types of discrimination migrants face including institutional bigotry, such as inequality of access to welfare and services, and interpersonal discrimination, which is observed during social encounters and interactions at the individual level [5, 9, 31]. The concept of self-perceptions of discrimination is often used in previous studies. Because people may take differences in perceiving a given situation as bigotry, the perceived discrimination may be different from actual discrimination [32]. Nonetheless, self-perceived discrimination is found negatively associated with health and well-being, though the perception of discrimination is not verified using actual events [5, 33]. Perceiving discrimination besides reflects people's cognitive appraisement of a given state of affairs, the self-report experiences tin be stressful, and thus it is worthwhile to examine the effects of perceived bigotry [33, 34]. Given the possible discrimination faced by rural-to-urban migrants, one aim of the current study was to define the effect of their perceived discrimination experience on the human relationship betwixt migration and health outcomes.

Discrimination and health condition

Discrimination feel has been identified as a risk cistron for poor wellness amongst minorities and immigrants in the existing literature [33, 35]. However, these studies take employed different measures of discrimination and health. The experience of discrimination is negatively associated with cocky-reported wellness. For case, a study using data on 7720 valid responses to the Longitudinal Survey of Immigrants to Canada revealed visible minorities and immigrants who had experienced discrimination or unfair treatment to be the most likely to experience a pass up in self-reported health condition in Canada [36]. Experience of discrimination is as well negatively associated with mental health and physical health. A literature review reported such experience to be associated with poor mental health outcomes among Latinos in the United states of america, with the studies reviewed employing measures of perceived discrimination, employment bigotry, and phenotype discrimination [37]. Unfair treatment was harmful to cardiovascular health, with cumulative unfair treatment associated with worse subclinical cardiovascular affliction among Caucasian women [38]. A study reviewing 62 empirical articles that had used different measures of discrimination experience plant such experience to be associated with poorer wellness among Asian Americans [35]. Most of the manufactures reviewed focused on mental health issues, although some examined the role of discrimination in physical wellness measures such as physical functioning, cardiovascular disease, and chronic physical condition. A meta-analytic review analyzed manufactures covering multiple forms of perceived discrimination and both mental and physical health outcomes and reported that perceived bigotry negatively influences both mental and concrete wellness [33]. Some scholars have also differentiated between direct targeted bigotry (i.e., that experienced personally) and ambient forms thereof (i.due east., witnessing, overhearing, or being aware of others' discrimination experience), with both forms associated with negative psychosocial outcomes [39].

The foregoing studies were all conducted among minorities or immigrants in the international context, while studies carried out in People's republic of china have besides revealed exposure to bigotry or unfair treatment to be associated with poor health among rural-to-urban migrants. Rural-to-urban migrants are confronted with a marginalized life in urban People's republic of china and, as a outcome, have poorer psychological health [9]. Employing data from a national household survey in 2009, it was found that perceived interpersonal discrimination has a more detrimental effect than perceived institutional discrimination on self-rated concrete health and depressive distress among rural-to-urban migrants [5]. Chen's measures of interpersonal and institutional discrimination focused on six types of behaviors and events, and the study left other types of discrimination unexamined and discrimination attributions unmentioned. A cross-sectional survey of 1006 rural-to-urban migrants in Beijing besides revealed experienced or perceived unfair treatment, including job and workplace discrimination, distrust, negative attitudes amidst others, and unfair treatment from local law enforcement, to be negatively linked to the quality of life, including overall well-being, general health, concrete health, psychological health, social relationships, and environment scores [vi]. Another analysis of cross-sectional data in Beijing likewise revealed that both experiences of discrimination and perceived social inequity were strongly related to the mental health problems of rural-to-urban migrants [24]. Nonetheless, the study sample was restricted to rural-to-urban migrants in Beijing, and the relationship betwixt discrimination and quality of life and mental health in these two studies was examined without a reference group. In summary, although previous studies have adopted unlike measures of unfair treatment and discrimination, exposure to unfair handling and discrimination is generally associated with poorer health, both in Red china and internationally.

Factors influencing migration decisions

Migrants tend to exist a cocky-selected group among those who determine to migrate. Thus, migration choice is non random, and factors, such as the pre-migration statuses of wellness and mental health that may back up a decision of migration are critical to be adjusted when testing the health consequences of migration [12]. Variables used in previous studies to predict migration decisions are included in this study, and these variables include gender, age, age squared, indigenous minority, instruction level, logarithm of household income, household size, and regions [12, 40, 41]. Wellness is identified to be an of import factor influencing migration decisions: individuals who report better health are more likely to drift [42, 43], and those who have poorer health are more likely to return to their hometown [42, 44]. In addition, compared with the outset-generation migrants, the new generation migrants are more willing and adaptable to stay in the city [45], and thus cohort is also included equally a determinant of migration. Considering unlike factors may influence migration decisions and further impact health condition after migration, item methods are required to reduce the selection bias earlier analyzing the relationship between migration and health.

Research gaps and hypotheses

The existing literature has revealed inconsistent health differences between migrants and non-migrants and identified the complicated influence of migration on health. Information technology is important to examine the relevant pathways on how migration exerts influence on health, and the current report hypothesizes that migration poses a negative affect on health and mental health in consideration of discrimination experience. Equally informed by the literature review, the indirect effect of bigotry experience on the human relationship betwixt migration and health status is underexplored. Also, migrants are a cocky-selected grouping. In order to rule out the possible selection bias earlier examining the health consequences of migration, a rigorous information analytical method, such as the propensity scoring method is adopted.

This study was designed to respond the following inquiry question: Does discrimination experience mediate the associations between migration status and wellness outcomes, such every bit cocky-reported health, mental health, and physical health? The study has three hypotheses: (1) Discrimination feel mediates the relationship between rural-to-urban migration and self-reported health. (2) Discrimination experience mediates the human relationship between rural-to-urban migration and mental wellness. (3) Discrimination experience mediates the relationship between rural-to-urban migration and physical wellness. Fig i depicts the hypothesized relationship among rural-to-urban migration, bigotry experience, and health outcomes.

Methods

Information

An ideals approval of the enquiry was granted by the Human Enquiry Ethics Committee (HREC), The Academy of Hong Kong (Reference No. EA1708010). China Family Panel Studies (CFPS), launched by the Peking Academy Institute of Social Science Survey (ISSS) in 2010, provide high-quality, nationally representative, longitudinal data [46]. The CFPS data tin be obtained from this website (https://opendata.pku.edu.cn). The topics covered by the CFPS surveys include economic status, educational activity, family dynamics and relationships, migration, and health, among others. The baseline survey was conducted in 2010, with split up follow-up surveys conducted in 2012, 2014, 2016, and 2018. The 2010 baseline survey adopted multi-stage (i.e., county, village, and household) probability-proportional-to-size sampling with implicit stratification. All members of sampled households anile ix or above were interviewed, with the total sample comprising 14,960 households and 33,600 adults from 635 communities across 25 provinces, municipalities, and autonomous regions [47].

Using information from the cantankerous-sectional component of the tertiary (2014) CFPS wave, this study examined whether discrimination experience mediates the relationship betwixt migration and health. Although CFPS 2014 does non provide the latest data, its measure of discrimination experience includes three answers (i.e., "neither heard nor experienced", "have heard about information technology, simply haven't experienced", and "have experienced"), whereas the mensurate in CFPS 2016 includes only two (i.e., have experienced and accept not experienced), and CFPS 2018 does not ask about respondents' bigotry experience. Hearing most discrimination in CFPS 2014 captures the experience of ambient forms of discrimination, and is associated with sensation of stigmatized status, anxiety, and depression [39, 48]. Thus, data from CFPS 2014 were used to conduct the analysis herein. Compared with the 2010 sample, the response charge per unit to the second follow-upwardly survey in 2014 was 79.3% [49], which is quite a loftier response rate. The analytical sample is limited to those who were inside working-age and even so participated in the labor marketplace. Respondents who were out of the labor market and who were younger than 16 or older than 60 were excluded.

Analytical strategy

Stata 16 was employed to deport the analysis. Descriptive analysis, chi-foursquare tests, and t-tests were first performed to show the general features of rural residents and rural-to-urban migrants. Then, to resolve rural-to-urban migration option bias, the PSM method was adopted, with propensity scores computed via logistic regression and i:1 nearest neighbor matching conducted with a caliper of 0.25*standard divergence (SD). Stata with "psmatch2" was used for PSM [50]. Samples whose propensity scores were beyond the common back up were excluded in the matching procedures. Co-ordinate to the previous research, this matching technique can match each rural-to-urban migrant with a rural resident with observable characteristics such that the probability of being a rural-to-urban migrant is very similar for the migrant and non-migrant [51]. Subsequently, the average treatment outcome of migration on bigotry experience and health can exist obtained by comparing the matched rural-to-urban migrants and rural residents in terms of their discrimination feel and health status.

Finally, regression and mediation analyses were conducted after PSM. For regression analysis, logistic regression was performed for self-reported wellness and concrete discomfort, whereas ordinary least squares (OLS) regression was performed for psychological distress and discrimination experience. For mediation analysis, the natural indirect effects (NIE) were computed through the "paramed" program in Stata [52, 53]. The NIE, formally divers as NIE = E[Y_oneM₁-Y₁M₀], compares the counterfactual outcome of the mediator value of X = i and X = 0, with the treatment status fixed as X = 1 [54, 55]. Specifically, NIE in this research answers this counterfactual question: If we were to agree migration status as rural-to-urban migration, what would be the effect on the health status of a change in the level of discrimination experience from the value realized for rural residents to the value realized for rural-to-urban migrants? Information technology evaluates how much the health outcomes would change on average if the rural-to-urban migration'due south influence exerted only through modifying the discrimination experience [55]. The NIE helps to compare the change of contrasting the discrimination experience with the exposure fixed at the rural-to-urban migration status. Examining the NIE helps us to understand how rural-to-urban migration negatively influences health outcomes through discrimination experience from the perspective of wellness depletion result, which has not been fully studied in previous research. Evaluating the NIE is policy relevance. If anti-discrimination practices and policies could be provided for the rural-to-urban migrants, their health outcomes may therefore be improved. Bootstrapping with one thousand replications was employed for the bias-corrected confidence interval (CI). The seed was set up as 1234. Linear regressions were performed to fit discrimination experience and psychological distress, and logistic regressions for such dichotomized outcomes every bit self-reported wellness and physical discomfort. No treatment-mediator interaction was included in the models.

Sensitivity analysis and results comparison are important in propensity score assay [56]. Different calipers were employed to perform the matching for the estimated propensity score. The first caliper was ready at the recommended size of a quarter of an SD of the estimated propensity score, whereas the narrowest caliper was set at 0.05 and the widest at 0.i and 0.five [56].

Only respondents with no missing values for the mediator, independent, dependent, and control variables were selected for information analysis. Unlike sets of control variables were employed in the propensity score ciphering and mediation analysis, as discussed in the post-obit section. For the chi-square tests, t-tests, and regression assay, coefficients with p values smaller than 0.05 were considered pregnant. For mediation analysis using bootstrapping, indirect effects were considered to exist if the 95% bias-corrected CI for the odds ratio (OR) did not contain the value of 1 [57] or that for the coefficients using linear regressions did not include the value of 0.

Variables

Independent variable.

Similar to other migration studies using national data [5, 58], migration status was differentiated by respondents' hukou status and residence during the survey period (in a rural or urban expanse) in this study. Although minimum migration time was non included in Chen's and Wang's definitions, being abroad from i's permanent hukou residence for at least six months was required to define a rural-to-urban migrant in this written report. Appropriately, rural residents are defined equally individuals who agree an agronomical hukou and live in a rural area, whereas rural-to-urban migrants are individuals who agree an agronomical hukou merely lived in an urban area for at to the lowest degree six months during the survey period. Individuals who remain in their rural locale were selected every bit a comparing group for rural-to-urban migrants to measure the health consequences of migration, as selecting those living in the urban destinations might not have immune us to differentiate between migration'south effects on health and preexisting wellness disparities betwixt the sending and receiving locales [10, 59].

Dependent variables.

Iii measures of health-related outcomes, namely, self-reported health, psychological distress, and physical discomfort, were included as dependent variables. Self-reported health was measured by a single item, "How would you rate your health status?", with the answers re-coded as a dichotomized variable (see Tabular array one). The six-item screening scale for psychological distress [60] was adopted to assess mental health. This scale measures respondents' frequency of feeling depressed, nervous, restless or fidgety, hopeless, and that everything was an try or meaningless during the by month, with the answers re-coded equally one = "Never," 2 = "Sometimes," 3 = "One-half the time," four = "Frequently," and 5 = "Virtually every day." The composite score was calculated by summing all of the items, and higher values bespeak the severity of psychological distress. The Cronbach'due south alpha among all adult respondents in 2014 was .858 (Northward = 31418). Finally, concrete discomfort was assessed past a single detail: "During the past two weeks, have you felt any physical discomfort?" This item shows the respondents' physical wellness. The coding values of answers were shown in Table 1.

Mediator.

Discrimination experience was measured by the experience of life events perceived to exist unfair and attributed to a specific cause such as inequality or hukou status. CFPS 2014 includes seven self-reported items concerning discrimination experienced in the by year: "Unfair treatment due to inequality betwixt the rich and the poor"; "Unfair treatment due to household registration status"; "Unfair treatment due to gender discrimination"; "Unfair handling by government officials"; "Disharmonize with authorities officials"; "Unreasonable delay and stalling at a regime agency"; and "Unreasonable charges paid to a government agency." The answers for each item were recoded as 0 = "Neither heard nor experienced," 1 = "Have heard about it, but haven't experienced," and 2 = "Have experienced." The composite score of the seven items was considered as a continuous variable, with an acceptable Cronbach's blastoff of .800 (Northward = 30105) amidst all adult respondents in 2014. Higher values betoken the severity of bigotry feel.

Control variables.

Basic demographic and socioeconomic variables were included as control variables, including gender, age, age squared, cohort, ethnicity, marital status, employment, didactics level, religious belief, medical insurance, logged per capita annual household income, household size, and regional information. These variables are commonly used in previous studies focusing on the health condition of migrants in Red china. Tabular array 1 shows the coding values of gender, cohort, ethnicity, employment status, medical insurance, and religious conventionalities, and the recategorized dummy variables of marital condition and education level. Household income was adapted by household size, i.east., net family unit income per capita (yuan) and naturally log-transformed. The value of "1" was added to the family income of all respondents to employ the log role. Household size refers to the number of family members who live in the household or who exercise not live at home but take close financial ties to other members such as many migrants. The household income and household size data were complemented with the family-level datasets. 4 dummy variables, namely, "Eastern Region," "Central Region," "Western Region," and "Northeast Region," were employed to represent the regions in which the respondents were surveyed. The "paramed" command uses the aforementioned set of covariates to guess two models: ane is for the mediator conditional on treatment and covariates, and the other one is for the outcome conditional on treatment, the mediator, and covariates [53].

A different set of variables was used to guess the propensity scores, including gender, historic period, age squared, cohort, ethnicity, marital condition, employment status, education level, natural log of net family income per capita, household size, and regional data, and self-reported change in health. Cocky-reported change in health was assessed by respondents' rating of their health status during the survey menses compared to the previous year (0 = "Worse," i = "No change," and ii = "Better").

Results

Descriptive statistics, chi-square tests, and t-tests before PSM

Descriptive analysis was offset conducted to define the differences between rural-to-urban migrants and rural residents. Tabular array 1 depicts the sample characteristics of migration statuses. It tin be seen that rural residents accounted for 92.93% of the sample (Due north = 8,228), with just 7.07% rural-to-urban migrants (N = 626). The migrants had higher proportions of good self-reported health (84.35%), and lower proportions of physical discomfort in the by two weeks (22.36%) than rural residents, simply there was no significant difference in psychological distress between the two groups (rural residents: Mean [1000] = 9.162 [SD = 3.826] versus rural-to-urban migrants: Grand = 9.149 [SD = 3.680]; p > 0.05). Still, the rural-to-urban migrants reported higher discrimination feel scores (Thou = 2.553 [SD = 3.048]) than the rural residents (Thou = 2.051 [SD = 2.959]). At that place were pregnant differences between the 2 groups for the majority of control variables except for gender, marital status, and religious belief. Detailed results are shown in Table 1.

Results of propensity score estimation

A propensity score was estimated via logistic regression using a set of variables that might explain why some people are more likely than others to become rural-to-urban migrants. Results of propensity score interpretation show that individuals who were female, in the middle age, belonged to the Han ethnicity, were divorced or widowed or married or cohabiting, had received 6–12 or 12+ years of schooling, and/or had a higher net family unit income per capita were more likely to be a rural-to-urban migrant than a rural resident. In dissimilarity, individuals who were younger or older, employed, living in a large household, and/or living in the Key Region or Western Region were less likely to be a rural-to-urban migrant. The detailed results are presented in S1 Table in the supporting information.

Samples whose propensity scores were beyond the mutual back up were excluded from the matching procedures. The common support of treated and untreated samples, the histograms of the estimated propensity scores by handling status, and the standardized % bias across covariates after PSM declined for all of the matched samples are provided in S1–S3 Figs, respectively, in the supporting information. The post-PSM chi-square tests and t-tests as well revealed no significant differences between rural residents and rural-to-urban migrants for any of the aforementioned variables used to define the determinants of rural-to-urban migrant status. The Rubin'southward B for the matched sample was 12.9, which is smaller than 25 and thus acceptable; the Rubin'southward R was 0.96, which is inside the adequate level of .5 to 2 [61, 62]. The combination of balancing tests constitute the balancing property to exist more often than not satisfied.

Results of regression and mediation analyses afterwards PSM

The new sample generated past PSM (rural residents: Northward = 609; rural-to-urban migrants: N = 609) was employed to conduct mediation analysis. Table 2 reports the associations between rural-to-urban migration and bigotry experience and the three measures of wellness. Rural-to-urban migration was positively linked to perceived discrimination experience (β = 0.768, p < 0.001), which indicates that rural-to-urban migrants reported more discrimination experience than rural residents. The associations betwixt migration and self-reported health (OR = 1.069, p > 0.05) and physical discomfort (OR = 1.169, p > 0.05) were not significant, whereas migration was positively associated with psychological distress (β = 0.516, p < 0.01).

Table 3 presents the results of mail-PSM mediation analysis. In general, the indirect effects of discrimination feel on the relationships between rural-to-urban migration and the 3 measures of health were significant in this analysis with controlling for relevant variables. More than specifically, holding migration condition as rural-to-urban migration, for a modify in the level of discrimination experienced from the value realized for rural residents to the value realized for rural-to-urban migrants, the OR of proficient self-reported health was 0.926 (95% CI: 0.868 0.969), indicating lower odds of good self-reported health for the migrants. Once more, holding migration status as rural-to-urban migration, for a change in the level of discrimination experienced from the value realized for rural residents to the value realized for rural-to-urban migrants, the value of psychological distress increased by 0.258 (95% CI: 0.152 0.409), and for a change in the level of discrimination experienced from the value realized for rural residents to the value realized for rural-to-urban migrants, the OR of physical discomfort was one.096 (95% CI: 1.042 i.171), indicating higher odds of reporting physical discomfort. In addition, the total effect of rural-to-urban migration on psychological distress was significant, and rural-to-urban migration lead to psychological distress increasing past 0.516 (95% CI: 0.114 0.895). Other furnishings were not significant.

Sensitivity assay

The results of sensitivity analysis using different calipers in PSM for regression assay and mediation analysis are presented in S2 and S3 Tables, respectively, in the supporting information. In full general, sensitivity assay after PSM using unlike calipers yielded similar results to that in which the caliper was set at 0.25*SD, thereby indicating the robustness of the results. For the regression analysis afterwards PSM using different calipers, rural-to-urban migration remained positively linked to discrimination experience and psychological distress, whereas post-PSM such arbitration analysis revealed discrimination feel to have meaning indirect effects on the relationship betwixt migration and three measures of wellness. The total effects of migration on psychological distress were also statistically significant.

Word

Cartoon on data from CFPS 2014, the study reported herein explored how rural-to-urban migration changes individuals' bigotry experience and to what extent such experience mediates the relationship between rural-to-urban migration and 3 measures of health. Previous research has documented the negative wellness impacts of bigotry experience, just the upshot of how discrimination feel mediates the relationship betwixt rural-to-urban migration and health outcomes, including self-reported health, psychological distress, and concrete discomfort, has been relatively neglected. The electric current research considered both ambient forms of discrimination and directly targeted bigotry in its measures of discrimination experience and provides the evidence needed to explore the indirect issue of such experience.

Few if any studies in the extant literature have resolved the possible self-selection bias in rural-to-urban migration condition earlier examining the potential relationship between migration and health. In this research, we estimated propensity scores to friction match each rural-to-urban migrant in our sample with a rural resident who had a similar probability of migration, thereby resolving the potential self-pick bias in such research [12]. Rural-to-urban migrants are a cocky-selected grouping, and factors such as health may influence individuals' migration decision and further influence their discrimination experience and health outcomes after migration. For example, if persons who have higher levels of education are more likely to migrate, and education level is related to health, so the health disparity between the migrants and non-migrants may not be the result of migration simply it is mixed with factors such as education level. Thus, migrants' self-selection bias is considered through conducting propensity score matching in this study. In add-on, we too conducted a sensitivity analysis by adopting unlike calipers in the matching procedures, thereby helping u.s. to compare our results and determine whether they are robust.

Post-PSM regression analysis demonstrated rural-to-urban migration to be positively associated with discrimination experience, with rural-to-urban migrants reporting more discrimination subsequently migrating to urban areas. This finding is inconsistent with Chen's study showing that migrants practice not perceive more discrimination than not-migrants with similar sociodemographic characteristics [five]. One possible explanation is that the 2 studies adopted dissimilar measures of discrimination, and Chen besides did not control for potential selection bias before comparing the discrimination experience of migrants and not-migrants. It is understandable that rural-to-urban migrants would report more discrimination experience than rural residents, as the latter accept fewer opportunities to communicate with urban residents and urban government agencies, and thus a more localized frame of reference concerning their circumstances [xxx].

Post-PSM mediation analysis revealed migration to exert a significant full effect on psychological distress, which indicates that rural-to-urban migration is related to higher values of psychological distress. However, the migration's total effects on self-reported wellness and concrete discomfort were not statistically significant. Psychological distress measures people'south mental status during the past calendar month, while self-reported health is a more than full general and longer-term mensurate of health, and concrete discomfort focuses exclusively on physical aspects of health in the by two weeks. The results suggest that experience of discrimination may have a more harmful effect on people's mental wellness rather than cocky-reported health and physical wellness. This is consistent with previous research that perceived discrimination is more strongly associated with mental wellness than physical health [63]. This research also identified significant indirect effects of bigotry experience on the relationship between migration and the three measures of health. Holding migration status as rural-to-urban migration, more experience of discrimination is linked to poorer wellness, including lower odds of self-reporting good wellness, higher scores of psychological distress, and higher odds of reporting concrete discomfort. Although the total furnishings of rural-to-urban migration on self-reported wellness and physical discomfort are not significant, it is withal necessary to examine the indirect effects of migration on health. Contempo research on mediation analysis besides recommends that a significant test for total effects should not exist employed equally a prerequisite for a examination of indirect furnishings in studies focusing on mediation alone [64]. Discrimination experience reflects how rural-to-urban migrants perceive unfair encounters in the context of social inequality and rural-urban disparities in China, thereby adding to our agreement of the health depletion effect of migration.

After rural individuals drift to urban areas, they have more than exposure to discrimination than previously, and those experiencing more than discrimination often have worse self-reported health, more psychological distress, and more than concrete discomfort. Appropriate practices and policies are thus required to bargain with unfair handling and discrimination during the process of rural-to-urban migration. The bigotry experience measured in the current research pertained to inequality between the rich and the poor, hukou status- and gender-based discrimination, and discrimination by authorities officials and government agencies. Thus, it is important to promote social equality, gender equality, and social inclusion. The reform of the hukou system and amend public welfare and social service arrangements are as well needed. Although the Chinese government has reformed the hukou system to establish a unified residential hukou without agricultural and non-agricultural types, welfare and social service reforms have non kept pace, meaning that rural-to-urban migrants still face a variety of institutional barriers and practice non have equal access to welfare. Further hukou reform is required to grant migrants easier and fairer access to public welfare and social services and to ensure equity in the provision of healthcare and public education to migrants and non-migrants [28, 65, 66]. In add-on, government officials should exist supervised to ensure that they provide a fair and reasonable service, and the work of government agencies should be evaluated in accordance with the rules of openness and transparency. It should also be noted that this report not only differentiated between "take experienced discrimination" and a lack thereof, but besides considered ambient forms of discrimination linked to awareness of stigmatized status, feet, and depression [39, 48]. Living in an surround in which ane hears near or witnesses others being treated unfairly may brand one feel anxious about his or her own disadvantaged position [39, 48]. Building a migrant-friendly environment is thus of the utmost importance.

Although information technology makes important contributions to the literature, this inquiry had several limitations that must be best-selling. First, rural residents may include both rural local residents and rural-to-rural migrants, and thus both were included in our group for comparison with rural-to-urban migrants. 2d, the data used in this research were cantankerous-sectional in nature, and thus only cantankerous-individual differences in discrimination experience and health were examined. Longitudinal mediation assay is required to exam how discrimination feel mediates the relationship between migration and health over the long term, with both cross-individual differences and individual change over time considered. Third, this research explored only whether the frequency of discrimination experience plays a office in the relationship between migration and health, with the indirect effects of specific types of discrimination experience on that relationship left unexamined. The style in which different types of discrimination experience influence the relationship between migration and health would exist a fruitful direction for future enquiry. In add-on, at that place may be other types of bigotry which are not included in the vii items. Including more types of bigotry experience would be helpful to examine the effects of discrimination. 4th, the three result variables, namely, SRH, psychological distress, and physical discomfort, were included in 3 independent models due to the limitation of using "paramed" that multiple outcomes cannot exist included simultaneously. Considering that the three event variables are associated with each other, employing them as mutually independent variables may effect in an inflation of Type I error. Fifth, every bit the CFPS adopts multi-phase probability sampling with implicit stratification, survey design effects (stratum, cluster, and individual weight) should have been included in estimating the parameters, but, technically, were non applied in our analysis. Every bit ii of the dependent variables, namely, self-reported health and physical discomfort, were dummy variables, "paramed" was adopted for arbitration analysis, simply does non support survey-weighted analysis [67, 68]. Given that it did not consider weight, stratification, or clustering, this research was unable to take total reward of the CFPS'south nationally representative sample, and the estimated parameters may too have reflected a certain degree of bias [69]. Sixth, although the method of propensity score matching has addressed the selection-bias for the migration status, the selection-bias for the mediator, i.e., bigotry experience, probably remained unresolved [70, 71]. It is noted that blending a not-randomized binary handling (migration status) and a non-randomized continuous mediator (discrimination experience) in the model may even so discipline to risk of self-selection bias. Nevertheless, this research controlled for variables influencing both migration status and discrimination experience, which blocked the back-door path from migration status to health outcomes [72]. Even so, although this research has controlled for many relevant variables, there may still be variables simply influencing the mediator and not influencing the treatment, and not decision-making for such variables may pb to a subtract of precision of the results to a sure extent [72]. Finally, this research was quantitative in nature. Obtaining qualitative information from rural-to-urban migrants and rural non-migrants would exist conducive to a ameliorate understanding of the complicated associations among migration, feel of unfair handling, and health.

Conclusions

From the perspective of the health depletion result, this inquiry examines whether the feel of discrimination mediates the relationship between rural-to-urban migration and three measures of wellness in consideration of migration pick bias. Afterwards migrating from rural to urban areas, individuals accept more than exposure to discrimination, which is harmful to their cocky-reported health, mental health, and physical wellness. Specifically, rural-to-urban migration is positively associated with psychological distress, and policies and practices, such as reform of welfare and services and edifice a migrant-friendly society, are needed to help rural-to-urban migrants cope with psychological distress during the process of migration. This research provides empirical evidence for reducing social and institutional discrimination against rural-to-urban migrants and ensuring them benefit from the social and economic development in China.

Supporting information

Acknowledgments

An earlier version of this commodity was presented at the 18th Almanac Research Postgraduate Conference at the Academy of Hong Kong. The authors would like to limited their gratitude to the audience members who provided helpful comments on the enquiry. The authors are also grateful to Byron Chiang for his technical advice on statistical modelling.

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