Behavioral Bridges to Health and Well-being: How Physical Activity Precedes Religious Participation in Mediating the Effects of Socioeconomic Status

Behavioral Bridges to Health and Well-being: How Physical Activity Precedes Religious Participation in Mediating the Effects of Socioeconomic Status | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Behavioral Bridges to Health and Well-being: How Physical Activity Precedes Religious Participation in Mediating the Effects of Socioeconomic Status Xiaotian Li, Guiping Zhao, Ruijie Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7577961/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background China's rapid socio-economic transformation has intensified social stratification and resource inequality, creating disparities in health outcomes and subjective well-being across different socioeconomic strata. While existing research has established the association between socioeconomic status (SES) and health outcomes, the behavioral mechanisms through which SES influences subjective health and happiness remain underexplored, particularly in the Chinese cultural context where physical activity and religious participation exhibit unique characteristics. Methods This study utilized nationally representative survey data from the Chinese General Social Survey (CGSS) and employed Generalized Structural Equation Modeling (GSEM) to examine the relationships among SES indicators (educational attainment, income, occupational prestige), lifestyle mediators (physical activity and religious participation), and outcome variables (subjective health and well-being). Conditional Mixed Process (CMP) Probit regression was conducted as a robustness check. The analysis controlled for demographic variables including gender, age, marital status, and regional factors. Results Educational attainment demonstrated the strongest positive associations with both subjective health and well-being, with college-educated individuals showing total associations of 1.046 for health and 1.294 for well-being. Physical activity emerged as a significant positive mediator, accounting for 60.9% and 46.4% of the total associations of junior high education with health and happiness, respectively. However, given the cross-sectional nature of this study, these findings represent associations rather than causal effects.For individuals with higher education, the mediation proportions reached 68.4% and 49.5%. Income showed consistent positive associations with both outcomes, with mediation effects of 32.9% for health and 44.5% for well-being. Occupational prestige exhibited complex patterns with mixed effects across equations. Contrary to Western findings, religious participation showed no significant positive effects on subjective health or well-being, reflecting the unique secular context of contemporary China. Gender differences revealed that females reported lower subjective health but higher happiness levels. Regional variations indicated that residents in Eastern and Central regions demonstrated different patterns of religious and physical activity participation compared to Western regions. Conclusions The study confirms that SES significantly influences subjective health and well-being through both direct pathways and behavioral mediators, with physical activity serving as a crucial transmission mechanism while religious participation lacks significant mediating effects in the Chinese context. These findings suggest that public health policies should prioritize improving access to physical activity opportunities across different socioeconomic strata while recognizing the limited role of religious engagement in promoting population well-being in secular societies. Social science/Anthropology Health sciences/Health care Humanities/Health humanities Biological sciences/Psychology Social science/Psychology Social science/Social policy Social science/Sociology socioeconomic status physical activity religious participation subjective health well-being structural equation modeling China Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1. Introduction Chinese society is undergoing a profound transformation from high-speed growth to high-quality development. However, accompanying these economic achievements is the increasing rigidity of social stratification and uneven resource distribution among social groups [ 1 – 2 ] . With deepening urbanization and industrial upgrading, distinct disparities are emerging among different social strata in education, income, occupational prestige, and social capital, weakening opportunities for social mobility [ 3 ] . This structural inequality influences not only material resources but also people's subjective perceptions and quality of life [ 4 ] . The "Healthy China 2030" strategy has elevated improving public health and well-being to a national priority [ 5 ] , highlighting the government's growing attention to health inequality. A key question remains unresolved: How do individuals from different socioeconomic status (SES) backgrounds transform structural resources into tangible health outcomes and happiness in everyday life? While extensive research has focused on SES impacts on health and happiness [ 6 ] , improving "resource accessibility" does not necessarily lead to corresponding rises in subjective well-being. The key lies in how individuals convert resources into psychological identification and emotional satisfaction through daily life practices [ 7 ] . Against the backdrop of economic growth and social transformation, the lifestyles of Chinese residents have become increasingly diversified [ 8 ] . Among lifestyle factors, physical activity and religious participation are two highly representative domains with significant cultural variation. Physical activity is widely regarded as positive behavior enhancing physical and mental health [ 9 ] . However, within social stratification frameworks, access to exercise varies significantly across SES groups due to occupational characteristics, economic conditions, and residential environments [ 10 ] . Higher-SES groups often enjoy greater accessibility to exercise, while lower socioeconomic groups may face higher opportunity costs, making it difficult to establish consistent exercise habits [ 11 ] . Chinese religious beliefs differ markedly from Western societies, exhibiting deinstitutionalization, ritualism, and localization characteristics [ 12 ] . Many folk beliefs focus more on community interaction and traditional ceremonies, serving as channels for social participation and spiritual support [ 13 ] . Therefore, religion's social functions and meanings in the Chinese context cannot be directly inferred from Western research results [ 14 ] . This study addresses the core question: Under what conditions does SES influence subjective health and happiness through the mediating roles of physical activity and religious participation? Specifically, are higher-SES individuals more capable of developing positive health behaviors and moderate religious practices, thereby attaining higher subjective well-being [ 15 ] ? Do these mechanisms differ across social groups and cultural contexts, demonstrating interactive or substitutive effects? These questions have practical relevance for social governance and public policy, particularly for targeted policies concerning sports infrastructure, community services, and religious affairs management under "Healthy China 2030" [ 16 ] . This inquiry enriches understanding of dynamic coupling among structure, behavior, and outcome, suggesting researchers should incorporate "lifestyle" as a meso-level factor when analyzing social stratification [ 17 ] . Given significant differences between Western and Chinese traditions regarding religion and physical activity, localized research perspectives are crucial for accurately interpreting how Chinese people construct meanings of "health" and "happiness" during social change. This study uses nationally representative survey data and applies Structural Equation Modeling (SEM) to test path relationships among relevant variables [ 18 ] , aiming to provide empirical support for the SES-lifestyle-well-being research paradigm while offering operational insights for policymakers. 2. Literature Review The relationship between socioeconomic status (SES) and individual health and happiness has long been one of the core topics in sociological research. Early scholars mostly approached this issue from the perspective of “social problems and governance,” viewing the distribution of health and disease as a consequence of social inequality, and emphasizing the critical role of structural factors in determining disease risk and subjective status assessments [ 19 – 20 ] . Related studies have also focused on disparities in access to medical and health resources among different groups, highlighting how inequality extends into everyday domains, including healthcare services and social stigma [ 21 ] . Building on this body of work, recent scholarship has increasingly shifted toward exploring the more nuanced mechanisms linking SES with health and happiness, especially examining how indicators such as education, income, and occupational prestige influence subjective well-being through specific mediating pathways such as lifestyle and social resources. 2.1 Education, Income, and Occupational Prestige: The Three Core Indicators of Socioeconomic Status Educational attainment is widely considered a critical element of SES. Research has shown that education directly improves health awareness and literacy, making individuals more likely to engage in positive health behaviors such as regular checkups, balanced diets, and cautious medication use [ 30 ] . Moreover, education indirectly enhances quality of life and subjective well-being through increasing income and social capital [ 31 ] . In the Chinese context, many scholars have found a stable positive correlation between moderate-to-high educational attainment and higher happiness among migrants, urban workers, and university graduates. The benefits of education are not limited to the economic level but also extend to social networks and modes of thinking. Individuals with higher education levels are more likely to access support and information through social channels, which may serve as buffers or protective factors for health and happiness [ 32 ] . Income is another core dimension through which SES influences health and happiness. Higher income typically implies more abundant material conditions and a greater ability to cope with life risks, significantly improving life satisfaction when per capita income remains modest [ 33 – 34 ] . However, once income reaches a certain level, its marginal utility for subjective well-being declines—a phenomenon known as the “Easterlin Paradox” [ 35 ] . Therefore, many researchers emphasize the need to account for the nonlinear effects of income across different stages: while income growth may bring substantial improvements for low- and middle-income groups, the happiness of high-income individuals tends to depend more on social recognition, job satisfaction, and spiritual pursuits [ 35 ] . This pattern has also been partially validated in recent Chinese studies. Although individuals with better economic conditions generally report better health, their happiness does not necessarily increase if they are burdened by growing social pressures and internal anxieties [ 36 ] . Sociological studies often regard occupational prestige as a core symbol of social status. It influences how individuals are respected in the workplace and social interactions, indirectly affecting their self-esteem, sense of self-worth, and social identity [ 37 ] . Existing research indicates that people in high-prestige occupations report higher happiness levels [ 38 ] . However, other studies have shown that the effects of occupational prestige may be attenuated when variables such as education and income are accounted for. Furthermore, when social or self-expectations become overly focused on external prestige, individuals may experience increased stress and responsibility, ultimately diminishing their happiness. 2.2 Lifestyle and Cultural Practices: Key Pathways Linking SES with Health and Happiness Sociological and anthropological inquiries into the relationship between governance and the governed have also echoed the profound influence of lifestyle factors on health disparities and everyday lived experience [ 39 ] . Resources and ideologies derived from SES often shape individuals’ lifestyles—including physical activity, leisure, and healthcare utilization—affecting subjective evaluations of health and happiness. Physical activity is considered one of the most important behavioral practices in health and happiness. Prior studies have shown that regular exercise improves bodily function, enhances social interaction, and effectively alleviates negative emotions such as anxiety and depression [ 40 ] . In urban Chinese society, relatively affluent and well-educated groups are more inclined to engage actively in sports activities [ 41 ] . These individuals often live and work in environments with better sports facilities and community resources, making accessing exercise opportunities easier. At the micro level, frequent exercise not only improves physical health but also fosters social cohesion and group belonging, combining “embodied practice” and “social interaction” to further enhance subjective well-being [ 42 ] . Religion, a practice rooted in culture and spirituality, is another important lifestyle dimension. However, its effects on health and happiness vary across social contexts [ 43 ] . In Western studies, religion is often associated with strong social support networks and coherent value systems, which benefit well-being. Nevertheless, researchers have observed contextual differences in China: on the one hand, Chinese society has undergone a long-term secularization process, and the reach of religion remains relatively limited [ 44 ] ; on the other hand, some individuals engage in religious activities more for ritualistic or social purposes, without sustained commitment to religious doctrines, thus failing to obtain long-lasting spiritual support [ 45 ] . Other scholars have found that in underdeveloped regions or among marginalized groups, religion may provide emotional comfort but cannot fully compensate for the health and happiness deficits caused by poverty or social exclusion [ 46 ] . 2.3 Socioeconomic Status, Health, and Happiness: The Extension of Structural Inequality Early research in sociology and anthropology on health and illness often employed concepts such as “inequality” and “structural violence,” emphasizing how disparities in SES and imbalances in resource distribution significantly affect disease risk and health evaluations [ 22 ] . Within this framework, SES encompasses measurable economic income, educational attainment, occupational hierarchy, power, and cultural capital. Numerous studies have found that individuals with higher educational levels, stable incomes, and better occupational conditions are more likely to access timely, high-quality healthcare and possess richer health knowledge and social support [ 23 – 24 ] . Therefore, people with higher SES generally report better subjective health and higher happiness levels. Another relevant research tradition has explored the chain of “SES → behaviors/attitudes → health/happiness,” examining how SES becomes coupled with health choices, psychological states, and social interaction practices [ 25 – 26 ] . These studies often emphasize that even after controlling for demographic variables such as age, gender, and residence, SES still exerts a significant and relatively stable influence on individuals’ physical and mental conditions. On one hand, SES determines access to life resources; conversely, it shapes life trajectories and future expectations. As scholars have noted, advantages associated with high SES tend to accumulate and become entrenched over time [ 27 – 28 ] . This cumulative effect suggests that individuals with higher social status often enjoy a “first-mover advantage” in health and happiness and show trajectories of sustained benefit [ 29 ] . 2.4 Theoretical Framework Based on the comprehensive literature review above, this study develops a conceptual framework to examine how socioeconomic status influences subjective health and well-being through lifestyle mediators. The proposed model integrates insights from social stratification theory and health behavior research to establish pathways linking structural resources to individual outcomes. Figure 1 presents the conceptual model guiding this investigation. The model posits that socioeconomic status, operationalized through education, income, and occupational prestige, influences subjective health and well-being through both direct pathways and indirect pathways mediated by physical activity and religious participation. Figure 1 illustrates the hypothesized relationships among socioeconomic status indicators, lifestyle mediators, and well-being outcomes. The framework includes three types of pathways: (1) Direct effects from SES components (education, income, occupational prestige) to outcome variables (self-rated health and subjective well-being); (2) Indirect effects through physical activity, where higher SES promotes exercise participation, which in turn enhances health and well-being; and (3) Indirect effects through religious participation, though this relationship may be more complex in contemporary societies where higher SES individuals may show different patterns of religious engagement.Based on this framework, we hypothesize that: (1) SES indicators will demonstrate significant direct effects on health and well-being; (2) physical activity will serve as a positive mediator linking SES to outcomes; and (3) religious participation will show variable mediating effects depending on cultural and social contexts. This model provides the theoretical foundation for the subsequent empirical analysis using Generalized Structural Equation Modeling. 3. Study Design and Participants 3.1 Data Source The China General Social Survey (CGSS) is a nationwide large-scale cross-sectional social survey project administered by the National Survey Research Center at Renmin University of China. This study utilized the merged dataset from 2015, 2017, and 2018 CGSS waves. The survey employed a multistage stratified probability sampling method to select nationally representative samples covering multiple dimensions of social attitudes, behavioral patterns, and living conditions among urban and rural residents. 3.2 Sample Selection Criteria To ensure data quality and analytical validity, we applied the following systematic exclusion criteria: (1) respondents with non-civilian household registration status including military registration, no household registration, or other unspecified registration types; (2) cases with missing or inconsistent educational background information; (3) respondents with implausible income values coded as "don't know", "refuse to answer", or other invalid responses; (4) participants with missing data on key health outcome variables including subjective health status and life satisfaction; (5) cases with missing information on mediator variables including religious participation and physical exercise engagement; (6) respondents with political party membership including Communist Party members, democratic party members, and other political affiliations to maintain sample homogeneity and control for potential political influences on health behaviors, retaining only those identified as "ordinary citizens" according to the CGSS coding scheme. After applying the aforementioned selection criteria, this study included 27,889 participants for analysis representing individuals without formal political party membership.The study population covered all provinces, municipalities, and autonomous regions nationwide, demonstrating good demographic representativeness. The sample encompassed adult residents across different age groups, educational levels, income strata, and geographical regions, providing sufficient statistical power for analyzing the mechanisms through which socioeconomic status affects health and well-being. 4. Research Findings Table 1 presents the distribution and central tendencies of the study variables, distinguishing among the dependent variables, mediating variables, key independent variables, and control variables.Self-rated health is measured as a continuous variable, with 55.04% of participants reporting above-average health status. Subjective well-being is similarly measured on a continuous scale, with 76.64% of respondents indicating above-average happiness levels.The mediating variables include physical activity and religious participation, both coded as binary variables. Among the participants, 51.36% reported engaging in physical activity, while 15.67% reported participation in religious activities. Regarding the independent variables, education level is categorized into three groups: “primary school or below,” “junior high school,” and “college or above,” with proportions of 42.01%, 46.58%, and 11.41%, respectively. Occupational prestige is treated as a continuous variable, with a mean value of 19.26 and a standard deviation of 18.62. Annual income means 26,252.6 (standard deviation = 32,494.6), while logarithmic income means 8.02 (standard deviation = 3.90). Meanwhile, the control variables include gender (44.36% male and 55.64% female), age groups (17–35 years: 19.66%, 36–59 years: 48.17%, 60 years and above: 32.17%), as well as a broad set of additional covariates such as household registration status (hukou), depressive symptoms, participation in social activities, internet use, perceived economic status, marital status, and political affiliation. Table 1 Descriptive Statistics Table Variable Category Variable Value/Scale Mean ± SD / % Variable Value/Scale Mean± SD / % Dependent Variables Self-Rated Health Continuous 55.04% Healthy Subjective Well-being Continuous 76.64% Happy Mediating Variables Physical Activity 0 = No 1 = Yes 51.36% Participate Religious Participation 0 = No 1 = Yes 15.67% Participate Independent Variables Educational Level 1 = Primary & below 2 = Middle School 3 = College & above 42.01% 46.58% 11.41% Occupational Prestige Continuous 19.26 ± 18.62 Income Continuous 26,252.6 ± 32,494.6 lnIncome Continuous 8.02 ± 3.90 Control Variables Gender 1 = Male 2 = Female 44.36% 55.64% Age 1 = 17–35 2 = 36–59 3 = 60+ 19.66% 48.17% 32.17% Hukou 0 = Rural 1 = Urban 32.77% Urban Depression Continuous 74.23% Depressed Social 0 = No 1 = Yes 88.75% Participate Internet 0 = No 1 = Yes 50.03% Use Perceived Economic Status 1 = Below Average 2 = Average 3 = Above Average 44.64% 49.50% 5.85% Marital Status 1 = UnMarried 2 = Married 3 = Divorced 4 = Widowed 6.98% 80.14% 2.52% 10.36% Political Affiliation 1 = Non-Party 100% Table 2 reports the estimation results derived from a Generalized Structural Equation Modeling (GSEM) framework, which includes four Logit regression equations corresponding to religious participation (react), physical activity (tycy), self-rated health (srh), and subjective well-being (swb). Within the model, the coefficients for both “junior high school” and “college and above,” in comparison to the reference group “primary school or below,” are statistically significant across both the mediating equations and the outcome equations. In the equation predicting religious participation, the coefficient for individuals with a junior high school education is − 0.270, statistically significant at the 1% level. This indicates a negative association between educational attainment and engagement in religious activities. Similarly, individuals with a college education or above exhibit a coefficient of − 0.172, also significantly negative, further suggesting that higher education levels are inversely related to the likelihood of participating in religious practices. Conversely, in the equation predicting physical activity, the coefficients for junior high school and college education are 0.885 and 2.086, respectively, both positive and statistically significant. These results imply that individuals with higher educational attainment are substantially more likely to engage in physical activity. Regarding health outcomes, the subjective health equation's coefficients for junior high school and college education are 0.202 and 0.331, respectively. In the subjective well-being equation, the corresponding coefficients are 0.314 and 0.654. These findings suggest that, as education level increases, individuals report better self-rated health and higher levels of subjective happiness. The logarithmic transformation of income is positively and significantly associated with participation in physical activity, self-rated health, and subjective well-being. However, its effect on religious participation is negligible, with a coefficient of − 0.001 that does not reach statistical significance. Occupational prestige exhibits mixed effects across the four equations. It shows a slight positive association in the religious participation equation and a slight negative association in the health equation. In the physical activity equation, the effect of occupational prestige is adverse, while in the subjective well-being equation, it is both positive and statistically significant. These results indicate that occupational prestige may contribute to well-being, although its influence on other behavioral or health-related outcomes appears more complex and less consistent. Control variables also reveal meaningful patterns. Gender is associated with a negative coefficient of − 0.161 in the health equation, suggesting that females report lower self-rated health. In contrast, the coefficient in the happiness equation is 0.203, indicating that females report higher levels of subjective well-being. Age and its squared term are statistically significant in the health and happiness equations, demonstrating a curvilinear relationship between age and these outcomes. In addition, regional characteristics, marital status, and the mediating variables—religious participation and physical activity—exhibit varied and differentiated effects across the four equations. These results further underscore the multidimensional pathways through which socioeconomic status and lifestyle factors interact to influence health and well-being. Table 2 Results of Generalized Structural Equation Modeling (GSEM) Variable Name Model 1 React Model 2 Tycy Model 3 Srh Model 4 Swb Junior high school -0.270*** (0.036) 0.885*** (0.027) 0.202*** (0.030) 0.314*** (0.034) College and Above -0.172*** (0.056) 2.086*** (0.052) 0.331*** (0.054) 0.654*** (0.062) ln(income) -0.001 (0.004) 0.053*** (0.003) 0.037*** (0.004) 0.020*** (0.004) Occupational Prestige (siops) 0.003*** (0.001) -0.005*** (0.001) -0.002*** (0.001) 0.002** (0.001) Female -0.161*** (0.027) 0.203*** (0.030) age -0.100*** (0.006) -0.064*** (0.006) age 2 0.000*** (0.000) 0.000*** (0.000) Eastern Region 0.020 (0.031) 0.089*** (0.034) Central Region 0.164*** (0.035) 0.176*** (0.039) Has Partner 0.230*** (0.036) 0.742*** (0.038) Religious Participation -0.056 (0.036) -0.003 (0.040) Physical activity 0.339*** (0.027) 0.307*** (0.030) Cons -1.584*** (0.043) -0.905*** (0.034) 2.953*** (0.146) 1.026*** (0.147) N 27,889 27,889 27,889 27,889 Note: Robust standard errors are reported in parentheses. * p < 0.10, ** p < 0.05, *** p < 0.01 Figure 2 visually presents the regression coefficients and their confidence intervals for all variables across the four GSEM equations in the form of a coefficient plot. The plot uses different symbols and colors to distinguish between the four models: Model 1 (religious participation equation), Model 2 (physical activity equation), Model 3 (subjective health equation), and Model 4 (subjective well-being equation). The figure clearly reveals several key patterns: (1) education variables show consistently negative associations with religious participation but positive associations with physical activity, health, and well-being; (2) income shows positive associations across most equations except religious participation; (3) gender effects vary across outcomes, with females showing lower health ratings but higher well-being; and (4) the broken axis design effectively accommodates the large variation in coefficient magnitudes, particularly for education variables in the physical activity equation.The figure clearly reveals significant directional differences for education variables (middle school and college & above) across equations: negative effects in the religious participation equation, while positive effects in the physical activity, subjective health, and subjective well-being equations. Additionally, the broken axis design effectively addresses differences in coefficient magnitudes, making smaller effect sizes clearly visible. Table 3 focuses on the decomposition of mediation effects from socioeconomic status—measured through educational attainment, income, and occupational prestige—on subjective health and well-being. The decomposition includes estimates of the indirect effect, direct effect, total effect, and the proportion of the effect mediated (Ratio). These estimates help to clarify the extent to which the influence of socioeconomic variables is channeled through the two mediators: religious participation and physical activity. For educational attainment, individuals with a junior high school education exhibit an indirect effect of 0.315 on self-rated health, while the direct effect is 0.202, resulting in a total effect of 0.517. The proportion of the total effect accounted for by the indirect pathway is 60.9%. A similar pattern is observed for subjective well-being: the indirect effect is 0.272, the direct effect is 0.314, and the total effect amounts to 0.586, yielding a mediated proportion of 46.4%. The effects of mediation are even more pronounced among individuals with a college degree or above. The indirect effect on health reaches 0.716, while the direct effect is 0.331, with a total effect of 1.046 and an indirect share of approximately 68.4%. In the case of subjective well-being, the indirect and direct effects are 0.640 and 0.654, respectively, leading to a total effect of 1.294 and a mediated proportion of 49.5%. Regarding income (measured in logarithmic form), the indirect effect on health is estimated at 0.018, while the direct effect is 0.037, resulting in a total effect of 0.054. The mediated proportion is 32.9% for health and 44.5% for subjective well-being, respectively. Occupational prestige shows a more nuanced pattern. For subjective health, the indirect effect is − 0.0018 and the direct effect is − 0.0022, leading to a total effect of − 0.0039, with 44.8% of the total effect mediated through the indirect pathway. However, the total effect for subjective well-being is nearly zero, resulting in an unstable or extreme ratio estimate lacking statistical interpretability. These decomposition results collectively reveal how different socioeconomic status dimensions influence health and happiness through two distinct lifestyle channels—religious participation and physical activity. The findings underscore the importance of accounting for behavioral and cultural mechanisms in understanding the social determinants of well-being. Table 3 Mediation Effects Summary Type Effect SRH Health SWB Happiness Junior High School Indirect Effect 0.315*** (0.028) 0.272*** (0.030) Direct Effect 0.202*** (0.030) 0.314*** (0.034) Total Effect 0.517*** (0.037) 0.586*** (0.042) Ratio 60.9% 46.4% College and Above Indirect Effect 0.716*** (0.060) 0.640*** (0.066) Direct Effect 0.331*** (0.054) 0.654*** (0.062) Total Effect 1.046*** (0.071) 1.294*** (0.081) Ratio 68.4% 49.5% Income Indirect Effect 0.018*** (0.002) 0.016*** (0.002) Direct Effect 0.037*** (0.004) 0.020*** (0.004) Total Effect 0.054*** (0.004) 0.036*** (0.004) Ratio 32.9% 44.5% Occupational Prestige Indirect Effect -0.001*** (0.000) -0.001*** (0.000) Direct Effect -0.002*** (0.0007) 0.001** (0.000) Total Effect -0.003*** (0.000) 0.000 (0.000) Ratio 44.8% Not Significant Figure 3 presents the decomposition results of indirect, direct, and total effects of socioeconomic status indicators on subjective health and happiness through a slope chart format. Solid lines represent effects on health, while dashed lines represent effects on happiness. The figure clearly shows that college & above education demonstrates the most significant total effects, followed by middle school education, while income and occupational prestige show relatively smaller effects. Notably, education variables exhibit substantial indirect effects, indicating that education primarily influences health and happiness through behavioral mediating factors (physical activity and religious participation), which is fully consistent with the mediation analysis results. Table 4 reports the results of a Conditional Mixed Process (CMP) Probit regression, in which four equations—religious participation, physical activity, subjective health, and subjective well-being—are estimated simultaneously. This approach allows for a robustness check of the overall model under a more stringent estimation framework. The results from the religious and physical activity equations show that both "junior high school" and "college and above" levels of education have consistent directional effects and statistically significant coefficients. Specifically, the "junior high school" coefficient in the religious participation equation is − 0.148, and for "college and above," it is − 0.083; both are negative. Conversely, the coefficients for physical activity are 0.548 and 1.240, respectively, indicating a strong positive relationship between educational attainment and the likelihood of engaging in exercise, while suggesting a reduced probability of religious participation among more educated individuals. Concerning the outcome variables—subjective health and subjective well-being—income and occupational prestige generally exhibit significant positive effects. Moreover, the effects of control variables such as gender and age are consistent with those observed in the previous GSEM analysis, further confirming the stability of the relationships. Overall, the CMP model estimates corroborate the findings derived from the GSEM framework, suggesting that the model specification is robust across different analytical approaches. Table 4 CMP Regression Results Variable/Equation Model 1 react Model 2 tycy Model 3 srh Model 4 swb Junior High School -0.148*** (0.020) 0.548*** (0.017) 0.240*** (0.037) 0.406*** (0.027) College and Above -0.083*** (0.031) 1.240*** (0.030) 0.420*** (0.077) 0.905*** (0.052) lnincome 0.000 (0.002) 0.030*** (0.002) 0.026*** (0.002) 0.023*** (0.002) Occupational Prestige -0.002*** (0.001) 0.004*** (0.001) 0.006*** (0.001) 0.001 (0.001) Female -0.087*** (0.016) 0.095*** (0.014) age -0.057*** (0.003) -0.028*** (0.003) age 2 0.000*** (0.000) 0.000*** (0.000) Eastern Region 0.011 (0.018) 0.044*** (0.016) Central Region 0.094*** (0.020) 0.083*** (0.018) Has Partner 0.135*** (0.021) 0.338*** (0.024) Religious Participation 0.066 (0.122) -0.224 (0.293) Physical activity -0.334** (0.162) -1.090*** (0.092) cons -0.928*** (0.022) -0.607*** (0.018) 1.770*** (0.085) 0.841*** (0.080) N 27,889 27,889 27,889 27,889 Note: Robust standard errors are reported in parentheses. p < 0.10, p < 0.05, p < 0.01. Figure 4 presents a forest plot of coefficients from the Conditional Mixed Process (CMP) robustness check. Through different colored dots and confidence intervals, the figure clearly illustrates the robustness of variable coefficients across the four equations. Compared with GSEM results, the CMP model coefficient estimates maintain high consistency in terms of directionality and significance, further validating the reliability of the research findings. Particularly noteworthy is that the differential effect patterns of education variables across equations are consistently confirmed in both analytical approaches, enhancing our confidence in the mechanisms through which socioeconomic status operates. Figure 5 employs a correlation coefficient heatmap to display the correlational relationships among residuals of the four GSEM models. The heatmap uses color intensity to represent correlation strength, with deep red indicating strong positive correlation and deep blue indicating strong negative correlation. The figure reveals strong positive correlations between Model 2 (physical activity) and Model 3 (subjective health) and Model 4 (subjective well-being) (0.63 and 0.96, respectively), reflecting the close connection between physical activity and health well-being. Conversely, Model 1 (religious participation) generally shows negative correlations with other models, consistent with our findings regarding the limited role of religious participation in the Chinese cultural context. Figure 6 demonstrates the nonlinear effects of age on subjective health and subjective happiness. The blue line represents the impact of age on subjective health, showing a continuous declining trend that reflects the gradual deterioration of physiological functions with aging. The orange line represents the impact of age on subjective happiness, displaying the classic U-shaped curve where happiness levels are relatively high in youth and old age but reach their lowest point in middle age. This finding is highly consistent with the famous "happiness U-curve" phenomenon in international research, revealing the complex patterns of happiness changes throughout the life course. To illustrate how including control variables and regional factors affects model fit and coefficient estimates, Tables 5, 6, and 7 present the results of three nested GSEM (Generalized Structural Equation Modeling) models. These models estimate coefficients across four equations: religious participation (react), physical activity (tycy), subjective health (srh), and subjective well-being (swb). Table 5 includes only socioeconomic status indicators—educational attainment (xueli3), logarithmic income (lnincome), and occupational prestige (siops)—along with the mediating variables. Table 6 builds upon this by incorporating demographic characteristics such as gender, age, and marital status. Table 7 further extends the model by including geographic regions (Eastern and Central), thereby allowing for an assessment of regional heterogeneity. Table 5 primarily captures the direct effects of education, income, and occupational prestige on religious participation and physical activity. Education exhibits consistently high and statistically significant coefficients in the subjective health and well-being equations. At the same time, income and occupational prestige display positive and negative associations with health and happiness, respectively. Table 6 demonstrates that, with the inclusion of demographic variables, the direction and significance of most core variables remain largely consistent with those in the baseline model, though some coefficient magnitudes change slightly. The coefficient for being female is positive in the religious participation equation, negative in the health equation, and positive in the happiness equation, indicating that gender exerts heterogeneous effects on both mediators and outcome variables. Table 7 , which presents the final model specification, reveals that individuals in Eastern and Central regions show significantly positive coefficients in religious participation and physical activity equations relative to those in Western regions. This finding suggests that regional differences in economic and cultural context positively influence individuals’ engagement in religious and exercise behaviors. The effects of regional variables on health and happiness are also differentiated, pointing to region-specific mechanisms in shaping individual well-being. Table 5 Nested GSEM (SES Only) Variable Model 1 React Model 2 Tycy Model 3 Srh Model 4 Swb Junior High School -0.270*** (0.036) 0.885*** (0.027) 0.619*** (0.027) 0.212*** (0.031) College and Above -0.172*** (0.056) 2.086*** (0.052) 1.189*** (0.048) 0.455*** (0.055) lnincome -0.001 (0.004) 0.052*** (0.003) 0.033*** (0.003) 0.012*** (0.004) Occupational Prestige 0.003*** (0.001) -0.005*** (0.001) -0.005*** (0.001) 0.001** (0.001) Religious Participation -0.047 (0.034) 0.014 (0.039) Physical activity 0.311*** (0.026) 0.305*** (0.030) _cons -1.584*** (0.042) -0.905*** (0.033) -0.522*** (0.033) 0.761*** (0.037) N 27,889 27,889 27,889 27,889 Note: Model 1 includes only the variables xueli3 (educational attainment), lnincome (logarithmic income), and siops (occupational prestige), along with the corresponding structural equations among the dependent variables. Table 6 Nested GSEM (SES + Demographics) Varible Model 1 React Model 2 Tycy Model 3 Srh Model 4 Swb Junior High School -0.251*** (0.038) 0.893*** (0.028) 0.201*** (0.029) 0.322*** (0.033) College and Above -0.195*** (0.063) 2.072*** (0.056) 0.325*** (0.053) 0.667*** (0.060) lnincome 0.007* (0.004) 0.056*** (0.003) 0.035*** (0.003) 0.020*** (0.003) Occupational Prestige 0.002*** (0.001) -0.00457*** (0.001) -0.002*** (0.001) 0.001** (0.000) Female 0.347*** (0.034) 0.151*** (0.026) -0.161*** (0.026) 0.206*** (0.029) age -0.002 (0.006) 0.001 (0.005) -0.099*** (0.005) -0.06344*** (0.00593) age 2 0.001 (0.000) -0.000 (0.000) 0.001*** (0.000) 0.001*** (0.000) Has Partner -0.056 (0.044) -0.056 (0.034) 0.233*** (0.035) 0.746*** (0.036) Religious Participation -0.048 (0.035) 0.003 (0.039) Physical activity 0.338*** (0.027) 0.310*** (0.030) _cons -1.719*** (0.1626) -0.973*** (0.124) 3.003*** (0.141) 1.089*** (0.143) N 27,889 27,889 27,889 27,889 Note: Model 2 builds upon Model 1 by adding control variables for gender, age, age squared, and marital status (Has Partner), in addition to the socioeconomic indicators and structural paths. Table 7 Nested GSEM (SES + Demographics + Region) Variable Model 1 React Model 2 Tycy Model 3 Srh Model 4 Swb Junior High School -0.259*** (0.039) 0.857*** (0.029) 0.202*** (0.030) 0.314*** (0.034) College and Above -0.206*** (0.064) 1.997*** (0.057) 0.331*** (0.054) 0.654*** (0.062) lnincome 0.008* (0.005) 0.055*** (0.003) 0.036*** (0.004) 0.020*** (0.004) Occupational Prestige 0.003*** (0.001) -0.005*** (0.001) -0.002*** (0.001) 0.002** (0.001) Female 0.345*** (0.035) 0.137*** (0.027) -0.161*** (0.027) 0.203*** (0.030) age -0.003 (0.007) 0.001 (0.005) -0.099*** (0.006) -0.064*** (0.006) age 2 0.000 (0.000) -0.000 (0.000) 0.000*** (0.000) 0.001*** (0.000) Eastern Region -0.064 (0.044) -0.059* (0.035) 0.230*** (0.036) 0.742*** (0.036) Central Region 0.1185*** (0.040) 0.312*** (0.030) 0.020 (0.031) 0.088*** (0.034) Has Partner 0.321*** (0.044) 0.149*** (0.034) 0.1644*** (0.035) 0.176*** (0.039) Religious Participation -0.056 (0.035) -0.003 (0.039) Physical activity 0.338*** (0.027) 0.306*** (0.030) _cons -1.8415*** (0.1642) -1.079*** (0.125) 2.952*** (0.142) 1.026*** (0.144) N 27,889 27,889 27,889 27,889 Note: Model 3 extends Model 2 by incorporating geographic region dummy variables to account for regional heterogeneity. Figure 7 compares the coefficient magnitudes of variables across three nested GSEM models through horizontal bar charts. The figure clearly illustrates the changing trends of core variable coefficients as control variables are progressively introduced. The figure shows that education variables (middle school and college & above) maintain relatively stable effect patterns across different models, indicating that the influence of education on health and happiness demonstrates strong robustness. Meanwhile, the inclusion of control variables such as marital status and regional differences reveals the complexity of socioeconomic status influence mechanisms, providing more detailed empirical evidence for understanding health inequality in the Chinese social context. Figure 8 employs smoothed line charts to display the coefficient change trajectories of four core socioeconomic status indicators across three nested models. The figure clearly shows that as demographic and regional variables are progressively controlled, each SES indicator exhibits different stability patterns. The coefficients for middle school and college & above education remain relatively stable across models, demonstrating the robustness of education effects; the coefficient for income (log) shows slight fluctuations but maintains overall consistent trends; occupational prestige coefficients remain relatively stable and close to the zero-effect line, which aligns with the complexity of occupational prestige effects we found in the main analysis. This progressive modeling approach effectively validates the robustness of the research findings. 5. Discussion The results of this study indicate that socioeconomic status (SES)—measured by educational attainment, income, and occupational prestige—has a statistically significant impact on subjective health and well-being through both direct effects and specific lifestyle mediators. Educational attainment plays a notable role in promoting individuals' perceived health and happiness. Research has shown that education directly improves health awareness and literacy, making individuals more likely to engage in positive health behaviors such as regular checkups, balanced diets, and cautious medication use [ 47 ] . Moreover, education indirectly enhances quality of life and subjective well-being through increasing income and social capital. In the Chinese context, studies have found a stable positive correlation between moderate-to-high educational attainment and higher happiness among migrants, urban workers, and university graduates [ 48 ] . The benefits of education extend beyond the economic level to social networks and modes of thinking, serving as buffers or protective factors for health and happiness [ 49 ] . Income is another core dimension through which SES influences health and happiness. Higher income typically implies more abundant material conditions and a greater ability to cope with life risks, significantly improving life satisfaction [ 50 ] . However, once income reaches a certain level, its marginal utility for subjective well-being declines—a phenomenon known as the "Easterlin Paradox" [ 51 ] . Many researchers emphasize the nonlinear effects of income: while income growth may bring substantial improvements for low- and middle-income groups, the happiness of high-income individuals tends to depend more on social recognition, job satisfaction, and spiritual pursuits [ 52 ] . This pattern has been partially validated in Chinese studies, where individuals with better economic conditions generally report better health, but their happiness does not necessarily increase if burdened by growing social pressures [ 53 ] . Occupational prestige is often regarded as a core symbol of social status, influencing how individuals are respected in workplace and social interactions, indirectly affecting their self-esteem, sense of self-worth, and social identity [ 54 ] . Existing research indicates that people in high-prestige occupations report higher happiness levels [ 55 ] . However, the effects of occupational prestige may be attenuated when variables such as education and income are controlled [ 56 ] . Furthermore, when social or self-expectations become overly focused on external prestige, individuals may experience increased stress and responsibility, ultimately diminishing their happiness [ 57 ] . This study examines the mediating roles of physical activity and religious participation in the relationship between SES and subjective health and happiness. Physical activity plays a significant positive mediating role. Individuals with higher SES—particularly those with more education—are more likely to engage in regular physical activity [ 58 ] . Those with higher education and income tend to have stronger health awareness and greater resources to invest in exercise, while individuals with higher social status often enjoy more leisure time and access to better fitness facilities [ 59 ] . These SES-based differences in exercise participation ultimately shape health and happiness outcomes [ 60 ] . The study finds that higher frequency and consistency of physical activity are associated with better subjective health and higher happiness levels. Exercise enhances physical and mental health, reduces illness risk, alleviates negative emotions such as anxiety and depression, and provides opportunities for social interaction and emotional uplift [ 61 ] . In contrast, religious participation demonstrates a more complex and less robust mediating role. Overall, this study finds that religious activity does not significantly affect subjective well-being and has a limited impact on subjective health. Frequent religious participation is not associated with higher happiness or better health outcomes in this context. This finding may appear inconsistent with Western literature, which emphasizes religion's positive role in providing emotional support, social connections, and meaning [ 62 ] . However, this study aligns with existing findings describing the contingent relationship between religion and well-being in the Chinese context [ 63 ] . Chinese religious beliefs differ markedly from Western societies, exhibiting deinstitutionalization, ritualism, and localization characteristics [ 64 ] . China follows a secular state model where religious belief is essentially personal choice and overall religiosity remains low [ 65 ] . Many individuals may only turn to religion during life crises rather than being regular practitioners [ 66 ] . "Religious participation without strong belief" is common in China, where people participate in religious ceremonies primarily out of custom or social obligation rather than genuine spiritual conviction [ 67 ] . Under these conditions, religious activities may not produce significant psychological benefits. Additionally, many religious participants belong to socially disadvantaged groups where spiritual solace cannot compensate for structural hardships such as poverty or poor health [ 68 ] . Control variables reveal meaningful patterns. Gender differences show females reporting lower subjective health but higher happiness levels, reflecting women's greater health awareness and stronger social support networks [ 69 ] . This gender paradox in well-being has been documented across multiple cultures, where women consistently report more negative affect but similar or higher levels of life satisfaction compared to men [ 70 ] . Age shows expected associations with both outcomes: subjective health evaluations decline with age due to physiological deterioration, while the relationship with happiness is more complex, suggesting psychological adaptation mechanisms [ 71 ] . Geographic region significantly influences health and well-being, with residents in economically developed areas generally reporting better subjective health due to superior healthcare resources and living conditions [ 72 ] . However, rapid urban development stress may partially offset happiness gains. Despite its contributions, the study has several limitations. The cross-sectional design limits causal inference capabilities, as reverse causality or omitted variable bias cannot be entirely excluded despite theoretical grounding and comprehensive covariate adjustment. Subjective health and happiness are self-reported indicators susceptible to individual interpretation and cultural norms. SES indicators have constraints—educational attainment cannot capture quality variations, income measures may omit assets and social benefits, and occupational prestige perceptions may vary across generations and regions. Additionally, specific marginalized populations may remain underrepresented, potentially affecting external validity. These findings have important implications for China's "Healthy China 2030" strategy. The strong mediating role of physical activity suggests that improving exercise accessibility across socioeconomic strata could effectively reduce health disparities. Public health policies should prioritize improving access to physical activity opportunities while recognizing the limited role of religious engagement in promoting population well-being in secular societies. These findings suggest that researchers should incorporate "lifestyle" as a meso-level factor when analyzing social stratification. Given significant differences between Western and Chinese traditions regarding religion and physical activity, localized research perspectives are crucial for accurately interpreting how Chinese people construct meanings of "health" and "happiness" during social change. 6. Conclusion This study reveals that socioeconomic status appears to shape subjective health and well-being among Chinese adults through a coupling mechanism of structure, behaviour, and outcome, with physical activity serving as an important mediating pathway in these relationships within the constraints of cross-sectional data. In contrast to Western research findings, religious participation exhibits different patterns of influence on health and happiness within China's secular cultural context, though this finding is limited by the behavioral measurement of religious participation rather than intrinsic religiosity. These conclusions should be interpreted cautiously given the study's cross-sectional design, specific sample characteristics, and cultural context, and may not generalize to other populations or time periods.These findings underscore the importance of understanding the coupling dynamics between social structure and individual outcomes, and highlight the need for culturally sensitive physical activity interventions tailored to different socioeconomic groups. Declarations Funding Statement: This work was supported by the National Social Science Foundation of China [24BTY085] under the project "Research on the Integrated Construction of Smart Sports in Chinese Universities." Ethics Declaration Ethics approval and consent to participate: This study utilized publicly available secondary data from the China General Social Survey (CGSS), which has received ethics approval from the Renmin University of China Ethics Committee. All CGSS participants provided informed consent. No additional ethics approval was required for this secondary data analysis. Consent for publication: Not applicable. Availability of data and materials: The datasets used in this study, specifically the 2015, 2017, and 2018 waves of the Chinese General Social Survey (CGSS), are publicly available for free download after simple registration on the official website of the Chinese National Survey Data Archive (CNSDA) at: http://cnsda.ruc.edu.cn/ . Competing interests: The authors declare that they have no competing interests. Author Contribution X.L. and G.Z. contributed equally as co-first authors to conceptualization, data collection and analysis, methodology development, and original draft writing. R.L. contributed to conceptualization and methodology, provided supervision and project administration. All authors reviewed and approved the final manuscript. 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Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 12 Mar, 2026 Reviews received at journal 26 Jan, 2026 Reviews received at journal 25 Jan, 2026 Reviewers agreed at journal 23 Jan, 2026 Reviewers agreed at journal 04 Jan, 2026 Reviewers invited by journal 14 Nov, 2025 Editor assigned by journal 14 Nov, 2025 Editor invited by journal 04 Nov, 2025 Submission checks completed at journal 20 Oct, 2025 First submitted to journal 20 Oct, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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14:06:26","extension":"xml","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":207324,"visible":true,"origin":"","legend":"","description":"","filename":"e9038e9446ca4239877922473b5e39d91structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/f96b21b34407e08a0f549333.xml"},{"id":96742046,"identity":"8d33fb8e-0390-4e8c-974f-ccf9432b5dc4","added_by":"auto","created_at":"2025-11-25 15:13:16","extension":"html","order_by":25,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":218204,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/83697793befc0a2ac15857aa.html"},{"id":96742016,"identity":"a9a3d80e-96a4-4126-b97d-308f742e7781","added_by":"auto","created_at":"2025-11-25 15:13:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54721,"visible":true,"origin":"","legend":"\u003cp\u003eConceptual Framework: The Mediating Role of Physical Activity and Religious Participation in the Relationship between Socioeconomic Status and Well-being Outcomes\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/f27c2c16631c2e835e0cab0e.jpg"},{"id":96913395,"identity":"6a8dd94a-2076-48c0-9070-eb2f06d17968","added_by":"auto","created_at":"2025-11-27 14:00:33","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":104443,"visible":true,"origin":"","legend":"\u003cp\u003eCoefficient Plot for GSEM Multiple Mediation Model (Adjusted with Broken Axis)\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/d166f41903e142badc778ab6.jpg"},{"id":96742018,"identity":"9207365f-bcf8-4f4d-b4d3-31be4f10ece6","added_by":"auto","created_at":"2025-11-25 15:13:15","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":95184,"visible":true,"origin":"","legend":"\u003cp\u003eOptimally Smoothed Slope Chart of Indirect, Direct, and Total Effects\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/63f407c49e21635a4d569d2b.jpg"},{"id":96914879,"identity":"c78f03ce-de13-4961-b508-0716e542d2b6","added_by":"auto","created_at":"2025-11-27 14:06:33","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90220,"visible":true,"origin":"","legend":"\u003cp\u003eForest Plot of Regression Coefficients with 95% Confidence Intervals\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/38a1014cf0897b9a2aac23d1.jpg"},{"id":96914125,"identity":"d441e88f-3141-43d7-a9df-acf044309332","added_by":"auto","created_at":"2025-11-27 14:05:29","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":66724,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation Heatmap (Nature Style)\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/0960e23015c55c60abc182ad.jpg"},{"id":96914461,"identity":"c64cda79-8e2e-46f7-9d3b-94bd353a4d6c","added_by":"auto","created_at":"2025-11-27 14:05:56","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":52334,"visible":true,"origin":"","legend":"\u003cp\u003eNonlinear Effect of Age on Health and Happiness\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/1b04612b7fa2318d20c6ab45.jpg"},{"id":96913629,"identity":"64038830-c255-44f4-9be6-97d74ba8aa34","added_by":"auto","created_at":"2025-11-27 14:03:14","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":93709,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Nested GSEM Models (SES Indicators)\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/236104dc5609564d228d862c.jpg"},{"id":96742024,"identity":"06835e56-2432-489e-883b-55dcfe72280d","added_by":"auto","created_at":"2025-11-25 15:13:15","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":58306,"visible":true,"origin":"","legend":"\u003cp\u003eFinal Smoothed Nested Regression Trend: Coefficient Changes Across Models\u003c/p\u003e","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/7ef3d4be560af92e5fc45039.jpg"},{"id":96922178,"identity":"f8515d55-626f-4080-96ba-42fa090659c5","added_by":"auto","created_at":"2025-11-27 14:18:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1982027,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7577961/v1/68aad6fa-7de3-4ee7-919e-123ed6896653.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Behavioral Bridges to Health and Well-being: How Physical Activity Precedes Religious Participation in Mediating the Effects of Socioeconomic Status","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eChinese society is undergoing a profound transformation from high-speed growth to high-quality development. However, accompanying these economic achievements is the increasing rigidity of social stratification and uneven resource distribution among social groups\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. With deepening urbanization and industrial upgrading, distinct disparities are emerging among different social strata in education, income, occupational prestige, and social capital, weakening opportunities for social mobility\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. This structural inequality influences not only material resources but also people's subjective perceptions and quality of life\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. The \"Healthy China 2030\" strategy has elevated improving public health and well-being to a national priority\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, highlighting the government's growing attention to health inequality.\u003c/p\u003e\u003cp\u003eA key question remains unresolved: How do individuals from different socioeconomic status (SES) backgrounds transform structural resources into tangible health outcomes and happiness in everyday life? While extensive research has focused on SES impacts on health and happiness\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, improving \"resource accessibility\" does not necessarily lead to corresponding rises in subjective well-being. The key lies in how individuals convert resources into psychological identification and emotional satisfaction through daily life practices\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Against the backdrop of economic growth and social transformation, the lifestyles of Chinese residents have become increasingly diversified\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAmong lifestyle factors, physical activity and religious participation are two highly representative domains with significant cultural variation. Physical activity is widely regarded as positive behavior enhancing physical and mental health\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. However, within social stratification frameworks, access to exercise varies significantly across SES groups due to occupational characteristics, economic conditions, and residential environments\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Higher-SES groups often enjoy greater accessibility to exercise, while lower socioeconomic groups may face higher opportunity costs, making it difficult to establish consistent exercise habits\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eChinese religious beliefs differ markedly from Western societies, exhibiting deinstitutionalization, ritualism, and localization characteristics\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Many folk beliefs focus more on community interaction and traditional ceremonies, serving as channels for social participation and spiritual support\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Therefore, religion's social functions and meanings in the Chinese context cannot be directly inferred from Western research results\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study addresses the core question: Under what conditions does SES influence subjective health and happiness through the mediating roles of physical activity and religious participation? Specifically, are higher-SES individuals more capable of developing positive health behaviors and moderate religious practices, thereby attaining higher subjective well-being\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e? Do these mechanisms differ across social groups and cultural contexts, demonstrating interactive or substitutive effects? These questions have practical relevance for social governance and public policy, particularly for targeted policies concerning sports infrastructure, community services, and religious affairs management under \"Healthy China 2030\"\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis inquiry enriches understanding of dynamic coupling among structure, behavior, and outcome, suggesting researchers should incorporate \"lifestyle\" as a meso-level factor when analyzing social stratification\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Given significant differences between Western and Chinese traditions regarding religion and physical activity, localized research perspectives are crucial for accurately interpreting how Chinese people construct meanings of \"health\" and \"happiness\" during social change. This study uses nationally representative survey data and applies Structural Equation Modeling (SEM) to test path relationships among relevant variables\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e, aiming to provide empirical support for the SES-lifestyle-well-being research paradigm while offering operational insights for policymakers.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eThe relationship between socioeconomic status (SES) and individual health and happiness has long been one of the core topics in sociological research. Early scholars mostly approached this issue from the perspective of \u0026ldquo;social problems and governance,\u0026rdquo; viewing the distribution of health and disease as a consequence of social inequality, and emphasizing the critical role of structural factors in determining disease risk and subjective status assessments \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Related studies have also focused on disparities in access to medical and health resources among different groups, highlighting how inequality extends into everyday domains, including healthcare services and social stigma\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. Building on this body of work, recent scholarship has increasingly shifted toward exploring the more nuanced mechanisms linking SES with health and happiness, especially examining how indicators such as education, income, and occupational prestige influence subjective well-being through specific mediating pathways such as lifestyle and social resources.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Education, Income, and Occupational Prestige: The Three Core Indicators of Socioeconomic Status\u003c/h2\u003e\u003cp\u003eEducational attainment is widely considered a critical element of SES. Research has shown that education directly improves health awareness and literacy, making individuals more likely to engage in positive health behaviors such as regular checkups, balanced diets, and cautious medication use \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. Moreover, education indirectly enhances quality of life and subjective well-being through increasing income and social capital \u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. In the Chinese context, many scholars have found a stable positive correlation between moderate-to-high educational attainment and higher happiness among migrants, urban workers, and university graduates. The benefits of education are not limited to the economic level but also extend to social networks and modes of thinking. Individuals with higher education levels are more likely to access support and information through social channels, which may serve as buffers or protective factors for health and happiness\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIncome is another core dimension through which SES influences health and happiness. Higher income typically implies more abundant material conditions and a greater ability to cope with life risks, significantly improving life satisfaction when per capita income remains modest\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. However, once income reaches a certain level, its marginal utility for subjective well-being declines\u0026mdash;a phenomenon known as the \u0026ldquo;Easterlin Paradox\u0026rdquo; \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Therefore, many researchers emphasize the need to account for the nonlinear effects of income across different stages: while income growth may bring substantial improvements for low- and middle-income groups, the happiness of high-income individuals tends to depend more on social recognition, job satisfaction, and spiritual pursuits\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. This pattern has also been partially validated in recent Chinese studies. Although individuals with better economic conditions generally report better health, their happiness does not necessarily increase if they are burdened by growing social pressures and internal anxieties\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSociological studies often regard occupational prestige as a core symbol of social status. It influences how individuals are respected in the workplace and social interactions, indirectly affecting their self-esteem, sense of self-worth, and social identity\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Existing research indicates that people in high-prestige occupations report higher happiness levels\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. However, other studies have shown that the effects of occupational prestige may be attenuated when variables such as education and income are accounted for. Furthermore, when social or self-expectations become overly focused on external prestige, individuals may experience increased stress and responsibility, ultimately diminishing their happiness.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Lifestyle and Cultural Practices: Key Pathways Linking SES with Health and Happiness\u003c/h2\u003e\u003cp\u003eSociological and anthropological inquiries into the relationship between governance and the governed have also echoed the profound influence of lifestyle factors on health disparities and everyday lived experience\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Resources and ideologies derived from SES often shape individuals\u0026rsquo; lifestyles\u0026mdash;including physical activity, leisure, and healthcare utilization\u0026mdash;affecting subjective evaluations of health and happiness.\u003c/p\u003e\u003cp\u003ePhysical activity is considered one of the most important behavioral practices in health and happiness. Prior studies have shown that regular exercise improves bodily function, enhances social interaction, and effectively alleviates negative emotions such as anxiety and depression\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. In urban Chinese society, relatively affluent and well-educated groups are more inclined to engage actively in sports activities\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e. These individuals often live and work in environments with better sports facilities and community resources, making accessing exercise opportunities easier. At the micro level, frequent exercise not only improves physical health but also fosters social cohesion and group belonging, combining \u0026ldquo;embodied practice\u0026rdquo; and \u0026ldquo;social interaction\u0026rdquo; to further enhance subjective well-being\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eReligion, a practice rooted in culture and spirituality, is another important lifestyle dimension. However, its effects on health and happiness vary across social contexts\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. In Western studies, religion is often associated with strong social support networks and coherent value systems, which benefit well-being. Nevertheless, researchers have observed contextual differences in China: on the one hand, Chinese society has undergone a long-term secularization process, and the reach of religion remains relatively limited\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e; on the other hand, some individuals engage in religious activities more for ritualistic or social purposes, without sustained commitment to religious doctrines, thus failing to obtain long-lasting spiritual support\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e. Other scholars have found that in underdeveloped regions or among marginalized groups, religion may provide emotional comfort but cannot fully compensate for the health and happiness deficits caused by poverty or social exclusion\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Socioeconomic Status, Health, and Happiness: The Extension of Structural Inequality\u003c/h2\u003e\u003cp\u003eEarly research in sociology and anthropology on health and illness often employed concepts such as \u0026ldquo;inequality\u0026rdquo; and \u0026ldquo;structural violence,\u0026rdquo; emphasizing how disparities in SES and imbalances in resource distribution significantly affect disease risk and health evaluations\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Within this framework, SES encompasses measurable economic income, educational attainment, occupational hierarchy, power, and cultural capital. Numerous studies have found that individuals with higher educational levels, stable incomes, and better occupational conditions are more likely to access timely, high-quality healthcare and possess richer health knowledge and social support \u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Therefore, people with higher SES generally report better subjective health and higher happiness levels.\u003c/p\u003e\u003cp\u003eAnother relevant research tradition has explored the chain of \u0026ldquo;SES \u0026rarr; behaviors/attitudes \u0026rarr; health/happiness,\u0026rdquo; examining how SES becomes coupled with health choices, psychological states, and social interaction practices\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. These studies often emphasize that even after controlling for demographic variables such as age, gender, and residence, SES still exerts a significant and relatively stable influence on individuals\u0026rsquo; physical and mental conditions. On one hand, SES determines access to life resources; conversely, it shapes life trajectories and future expectations. As scholars have noted, advantages associated with high SES tend to accumulate and become entrenched over time\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. This cumulative effect suggests that individuals with higher social status often enjoy a \u0026ldquo;first-mover advantage\u0026rdquo; in health and happiness and show trajectories of sustained benefit\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Theoretical Framework\u003c/h2\u003e\u003cp\u003eBased on the comprehensive literature review above, this study develops a conceptual framework to examine how socioeconomic status influences subjective health and well-being through lifestyle mediators. The proposed model integrates insights from social stratification theory and health behavior research to establish pathways linking structural resources to individual outcomes. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the conceptual model guiding this investigation. The model posits that socioeconomic status, operationalized through education, income, and occupational prestige, influences subjective health and well-being through both direct pathways and indirect pathways mediated by physical activity and religious participation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the hypothesized relationships among socioeconomic status indicators, lifestyle mediators, and well-being outcomes. The framework includes three types of pathways: (1) Direct effects from SES components (education, income, occupational prestige) to outcome variables (self-rated health and subjective well-being); (2) Indirect effects through physical activity, where higher SES promotes exercise participation, which in turn enhances health and well-being; and (3) Indirect effects through religious participation, though this relationship may be more complex in contemporary societies where higher SES individuals may show different patterns of religious engagement.Based on this framework, we hypothesize that: (1) SES indicators will demonstrate significant direct effects on health and well-being; (2) physical activity will serve as a positive mediator linking SES to outcomes; and (3) religious participation will show variable mediating effects depending on cultural and social contexts. This model provides the theoretical foundation for the subsequent empirical analysis using Generalized Structural Equation Modeling.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Study Design and Participants","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Data Source\u003c/h2\u003e\u003cp\u003eThe China General Social Survey (CGSS) is a nationwide large-scale cross-sectional social survey project administered by the National Survey Research Center at Renmin University of China. This study utilized the merged dataset from 2015, 2017, and 2018 CGSS waves. The survey employed a multistage stratified probability sampling method to select nationally representative samples covering multiple dimensions of social attitudes, behavioral patterns, and living conditions among urban and rural residents.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Sample Selection Criteria\u003c/h2\u003e\u003cp\u003eTo ensure data quality and analytical validity, we applied the following systematic exclusion criteria: (1) respondents with non-civilian household registration status including military registration, no household registration, or other unspecified registration types; (2) cases with missing or inconsistent educational background information; (3) respondents with implausible income values coded as \"don't know\", \"refuse to answer\", or other invalid responses; (4) participants with missing data on key health outcome variables including subjective health status and life satisfaction; (5) cases with missing information on mediator variables including religious participation and physical exercise engagement; (6) respondents with political party membership including Communist Party members, democratic party members, and other political affiliations to maintain sample homogeneity and control for potential political influences on health behaviors, retaining only those identified as \"ordinary citizens\" according to the CGSS coding scheme. After applying the aforementioned selection criteria, this study included 27,889 participants for analysis representing individuals without formal political party membership.The study population covered all provinces, municipalities, and autonomous regions nationwide, demonstrating good demographic representativeness. The sample encompassed adult residents across different age groups, educational levels, income strata, and geographical regions, providing sufficient statistical power for analyzing the mechanisms through which socioeconomic status affects health and well-being.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Research Findings","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the distribution and central tendencies of the study variables, distinguishing among the dependent variables, mediating variables, key independent variables, and control variables.Self-rated health is measured as a continuous variable, with 55.04% of participants reporting above-average health status. Subjective well-being is similarly measured on a continuous scale, with 76.64% of respondents indicating above-average happiness levels.The mediating variables include physical activity and religious participation, both coded as binary variables. Among the participants, 51.36% reported engaging in physical activity, while 15.67% reported participation in religious activities.\u003c/p\u003e\u003cp\u003eRegarding the independent variables, education level is categorized into three groups: \u0026ldquo;primary school or below,\u0026rdquo; \u0026ldquo;junior high school,\u0026rdquo; and \u0026ldquo;college or above,\u0026rdquo; with proportions of 42.01%, 46.58%, and 11.41%, respectively. Occupational prestige is treated as a continuous variable, with a mean value of 19.26 and a standard deviation of 18.62. Annual income means 26,252.6 (standard deviation\u0026thinsp;=\u0026thinsp;32,494.6), while logarithmic income means 8.02 (standard deviation\u0026thinsp;=\u0026thinsp;3.90).\u003c/p\u003e\u003cp\u003eMeanwhile, the control variables include gender (44.36% male and 55.64% female), age groups (17\u0026ndash;35 years: 19.66%, 36\u0026ndash;59 years: 48.17%, 60 years and above: 32.17%), as well as a broad set of additional covariates such as household registration status (hukou), depressive symptoms, participation in social activities, internet use, perceived economic status, marital status, and political affiliation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive Statistics Table\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable Category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eValue/Scale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD / %\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eValue/Scale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMean\u0026plusmn;\u003c/p\u003e\u003cp\u003eSD / %\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent Variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSelf-Rated Health\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55.04% Healthy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSubjective Well-being\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e76.64% Happy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMediating Variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePhysical Activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u0026thinsp;=\u0026thinsp;No\u003c/p\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e51.36% Participate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eReligious Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u0026thinsp;=\u0026thinsp;No\u003c/p\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15.67% Participate\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eIndependent Variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducational Level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Primary \u0026amp; below\u003c/p\u003e\u003cp\u003e2\u0026thinsp;=\u0026thinsp;Middle School\u003c/p\u003e\u003cp\u003e3\u0026thinsp;=\u0026thinsp;College \u0026amp; above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e42.01%\u003c/p\u003e\u003cp\u003e46.58%\u003c/p\u003e\u003cp\u003e11.41%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOccupational Prestige\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.26\u0026thinsp;\u0026plusmn;\u0026thinsp;18.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26,252.6\u0026thinsp;\u0026plusmn;\u0026thinsp;32,494.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003elnIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8.02\u0026thinsp;\u0026plusmn;\u0026thinsp;3.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eControl Variables\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Male\u003c/p\u003e\u003cp\u003e2\u0026thinsp;=\u0026thinsp;Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.36%\u003c/p\u003e\u003cp\u003e55.64%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;17\u0026ndash;35\u003c/p\u003e\u003cp\u003e2\u0026thinsp;=\u0026thinsp;36\u0026ndash;59\u003c/p\u003e\u003cp\u003e3\u0026thinsp;=\u0026thinsp;60+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19.66%\u003c/p\u003e\u003cp\u003e48.17%\u003c/p\u003e\u003cp\u003e32.17%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHukou\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u0026thinsp;=\u0026thinsp;Rural\u003c/p\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Urban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32.77% Urban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDepression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eContinuous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e74.23% Depressed\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSocial\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u0026thinsp;=\u0026thinsp;No\u003c/p\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e88.75% Participate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eInternet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u0026thinsp;=\u0026thinsp;No\u003c/p\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Yes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50.03%\u003c/p\u003e\u003cp\u003eUse\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePerceived Economic Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Below Average\u003c/p\u003e\u003cp\u003e2\u0026thinsp;=\u0026thinsp;Average\u003c/p\u003e\u003cp\u003e3\u0026thinsp;=\u0026thinsp;Above Average\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.64%\u003c/p\u003e\u003cp\u003e49.50%\u003c/p\u003e\u003cp\u003e5.85%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMarital Status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;UnMarried\u003c/p\u003e\u003cp\u003e2\u0026thinsp;=\u0026thinsp;Married\u003c/p\u003e\u003cp\u003e3\u0026thinsp;=\u0026thinsp;Divorced\u003c/p\u003e\u003cp\u003e4\u0026thinsp;=\u0026thinsp;Widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6.98%\u003c/p\u003e\u003cp\u003e80.14%\u003c/p\u003e\u003cp\u003e2.52%\u003c/p\u003e\u003cp\u003e10.36%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePolitical Affiliation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\u0026thinsp;=\u0026thinsp;Non-Party\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e reports the estimation results derived from a Generalized Structural Equation Modeling (GSEM) framework, which includes four Logit regression equations corresponding to religious participation (react), physical activity (tycy), self-rated health (srh), and subjective well-being (swb). Within the model, the coefficients for both \u0026ldquo;junior high school\u0026rdquo; and \u0026ldquo;college and above,\u0026rdquo; in comparison to the reference group \u0026ldquo;primary school or below,\u0026rdquo; are statistically significant across both the mediating equations and the outcome equations.\u003c/p\u003e\u003cp\u003eIn the equation predicting religious participation, the coefficient for individuals with a junior high school education is \u0026minus;\u0026thinsp;0.270, statistically significant at the 1% level. This indicates a negative association between educational attainment and engagement in religious activities. Similarly, individuals with a college education or above exhibit a coefficient of \u0026minus;\u0026thinsp;0.172, also significantly negative, further suggesting that higher education levels are inversely related to the likelihood of participating in religious practices. Conversely, in the equation predicting physical activity, the coefficients for junior high school and college education are 0.885 and 2.086, respectively, both positive and statistically significant. These results imply that individuals with higher educational attainment are substantially more likely to engage in physical activity.\u003c/p\u003e\u003cp\u003eRegarding health outcomes, the subjective health equation's coefficients for junior high school and college education are 0.202 and 0.331, respectively. In the subjective well-being equation, the corresponding coefficients are 0.314 and 0.654. These findings suggest that, as education level increases, individuals report better self-rated health and higher levels of subjective happiness.\u003c/p\u003e\u003cp\u003eThe logarithmic transformation of income is positively and significantly associated with participation in physical activity, self-rated health, and subjective well-being. However, its effect on religious participation is negligible, with a coefficient of \u0026minus;\u0026thinsp;0.001 that does not reach statistical significance. Occupational prestige exhibits mixed effects across the four equations. It shows a slight positive association in the religious participation equation and a slight negative association in the health equation. In the physical activity equation, the effect of occupational prestige is adverse, while in the subjective well-being equation, it is both positive and statistically significant. These results indicate that occupational prestige may contribute to well-being, although its influence on other behavioral or health-related outcomes appears more complex and less consistent.\u003c/p\u003e\u003cp\u003eControl variables also reveal meaningful patterns. Gender is associated with a negative coefficient of \u0026minus;\u0026thinsp;0.161 in the health equation, suggesting that females report lower self-rated health. In contrast, the coefficient in the happiness equation is 0.203, indicating that females report higher levels of subjective well-being. Age and its squared term are statistically significant in the health and happiness equations, demonstrating a curvilinear relationship between age and these outcomes. In addition, regional characteristics, marital status, and the mediating variables\u0026mdash;religious participation and physical activity\u0026mdash;exhibit varied and differentiated effects across the four equations. These results further underscore the multidimensional pathways through which socioeconomic status and lifestyle factors interact to influence health and well-being.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of Generalized Structural Equation Modeling (GSEM)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003eReact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003eTycy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003eSrh\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 4\u003c/p\u003e\u003cp\u003eSwb\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior high school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.270***\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.885***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.202***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.314***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.172***\u003c/p\u003e\u003cp\u003e(0.056)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.086***\u003c/p\u003e\u003cp\u003e(0.052)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.331***\u003c/p\u003e\u003cp\u003e(0.054)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.654***\u003c/p\u003e\u003cp\u003e(0.062)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eln(income)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.053***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.037***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.020***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational Prestige (siops)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.003***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.005***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.002***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.002**\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.161***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.203***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.100***\u003c/p\u003e\u003cp\u003e(0.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.064***\u003c/p\u003e\u003cp\u003e(0.006)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.000***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEastern Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003cp\u003e(0.031)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.089***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.164***\u003c/p\u003e\u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.176***\u003c/p\u003e\u003cp\u003e(0.039)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHas Partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.230***\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.742***\u003c/p\u003e\u003cp\u003e(0.038)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReligious Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.003\u003c/p\u003e\u003cp\u003e(0.040)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.339***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.307***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCons\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.584***\u003c/p\u003e\u003cp\u003e(0.043)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.905***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.953***\u003c/p\u003e\u003cp\u003e(0.146)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.026***\u003c/p\u003e\u003cp\u003e(0.147)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Robust standard errors are reported in parentheses. * p\u0026thinsp;\u0026lt;\u0026thinsp;0.10,\u0026emsp;** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05,\u0026emsp;*** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e visually presents the regression coefficients and their confidence intervals for all variables across the four GSEM equations in the form of a coefficient plot. The plot uses different symbols and colors to distinguish between the four models: Model 1 (religious participation equation), Model 2 (physical activity equation), Model 3 (subjective health equation), and Model 4 (subjective well-being equation). The figure clearly reveals several key patterns: (1) education variables show consistently negative associations with religious participation but positive associations with physical activity, health, and well-being; (2) income shows positive associations across most equations except religious participation; (3) gender effects vary across outcomes, with females showing lower health ratings but higher well-being; and (4) the broken axis design effectively accommodates the large variation in coefficient magnitudes, particularly for education variables in the physical activity equation.The figure clearly reveals significant directional differences for education variables (middle school and college \u0026amp; above) across equations: negative effects in the religious participation equation, while positive effects in the physical activity, subjective health, and subjective well-being equations. Additionally, the broken axis design effectively addresses differences in coefficient magnitudes, making smaller effect sizes clearly visible.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e focuses on the decomposition of mediation effects from socioeconomic status\u0026mdash;measured through educational attainment, income, and occupational prestige\u0026mdash;on subjective health and well-being. The decomposition includes estimates of the indirect effect, direct effect, total effect, and the proportion of the effect mediated (Ratio). These estimates help to clarify the extent to which the influence of socioeconomic variables is channeled through the two mediators: religious participation and physical activity.\u003c/p\u003e\u003cp\u003eFor educational attainment, individuals with a junior high school education exhibit an indirect effect of 0.315 on self-rated health, while the direct effect is 0.202, resulting in a total effect of 0.517. The proportion of the total effect accounted for by the indirect pathway is 60.9%. A similar pattern is observed for subjective well-being: the indirect effect is 0.272, the direct effect is 0.314, and the total effect amounts to 0.586, yielding a mediated proportion of 46.4%.\u003c/p\u003e\u003cp\u003eThe effects of mediation are even more pronounced among individuals with a college degree or above. The indirect effect on health reaches 0.716, while the direct effect is 0.331, with a total effect of 1.046 and an indirect share of approximately 68.4%. In the case of subjective well-being, the indirect and direct effects are 0.640 and 0.654, respectively, leading to a total effect of 1.294 and a mediated proportion of 49.5%.\u003c/p\u003e\u003cp\u003eRegarding income (measured in logarithmic form), the indirect effect on health is estimated at 0.018, while the direct effect is 0.037, resulting in a total effect of 0.054. The mediated proportion is 32.9% for health and 44.5% for subjective well-being, respectively.\u003c/p\u003e\u003cp\u003eOccupational prestige shows a more nuanced pattern. For subjective health, the indirect effect is \u0026minus;\u0026thinsp;0.0018 and the direct effect is \u0026minus;\u0026thinsp;0.0022, leading to a total effect of \u0026minus;\u0026thinsp;0.0039, with 44.8% of the total effect mediated through the indirect pathway. However, the total effect for subjective well-being is nearly zero, resulting in an unstable or extreme ratio estimate lacking statistical interpretability.\u003c/p\u003e\u003cp\u003eThese decomposition results collectively reveal how different socioeconomic status dimensions influence health and happiness through two distinct lifestyle channels\u0026mdash;religious participation and physical activity. The findings underscore the importance of accounting for behavioral and cultural mechanisms in understanding the social determinants of well-being.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMediation Effects Summary\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eType\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEffect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSRH Health\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSWB Happiness\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eJunior High School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.315***\u003c/p\u003e\u003cp\u003e(0.028)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.272***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.202***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.314***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.517***\u003c/p\u003e\u003cp\u003e(0.037)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.586***\u003c/p\u003e\u003cp\u003e(0.042)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRatio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eCollege and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.716***\u003c/p\u003e\u003cp\u003e(0.060)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.640***\u003c/p\u003e\u003cp\u003e(0.066)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.331***\u003c/p\u003e\u003cp\u003e(0.054)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.654***\u003c/p\u003e\u003cp\u003e(0.062)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.046***\u003c/p\u003e\u003cp\u003e(0.071)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.294***\u003c/p\u003e\u003cp\u003e(0.081)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRatio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.4%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e49.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eIncome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.018***\u003c/p\u003e\u003cp\u003e(0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.016***\u003c/p\u003e\u003cp\u003e(0.002)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.037***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.054***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.036***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRatio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32.9%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eOccupational Prestige\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIndirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.001***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.001***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDirect Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.002***\u003c/p\u003e\u003cp\u003e(0.0007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001**\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.003***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRatio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNot Significant\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the decomposition results of indirect, direct, and total effects of socioeconomic status indicators on subjective health and happiness through a slope chart format. Solid lines represent effects on health, while dashed lines represent effects on happiness. The figure clearly shows that college \u0026amp; above education demonstrates the most significant total effects, followed by middle school education, while income and occupational prestige show relatively smaller effects. Notably, education variables exhibit substantial indirect effects, indicating that education primarily influences health and happiness through behavioral mediating factors (physical activity and religious participation), which is fully consistent with the mediation analysis results.\u003c/p\u003e\u003cp\u003eTable 4 reports the results of a Conditional Mixed Process (CMP) Probit regression, in which four equations\u0026mdash;religious participation, physical activity, subjective health, and subjective well-being\u0026mdash;are estimated simultaneously. This approach allows for a robustness check of the overall model under a more stringent estimation framework.\u003c/p\u003e\u003cp\u003eThe results from the religious and physical activity equations show that both \"junior high school\" and \"college and above\" levels of education have consistent directional effects and statistically significant coefficients. Specifically, the \"junior high school\" coefficient in the religious participation equation is \u0026minus;\u0026thinsp;0.148, and for \"college and above,\" it is \u0026minus;\u0026thinsp;0.083; both are negative. Conversely, the coefficients for physical activity are 0.548 and 1.240, respectively, indicating a strong positive relationship between educational attainment and the likelihood of engaging in exercise, while suggesting a reduced probability of religious participation among more educated individuals.\u003c/p\u003e\u003cp\u003eConcerning the outcome variables\u0026mdash;subjective health and subjective well-being\u0026mdash;income and occupational prestige generally exhibit significant positive effects. Moreover, the effects of control variables such as gender and age are consistent with those observed in the previous GSEM analysis, further confirming the stability of the relationships.\u003c/p\u003e\u003cp\u003eOverall, the CMP model estimates corroborate the findings derived from the GSEM framework, suggesting that the model specification is robust across different analytical approaches.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCMP Regression Results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable/Equation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003ereact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003etycy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003esrh\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 4\u003c/p\u003e\u003cp\u003eswb\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior High School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.148***\u003c/p\u003e\u003cp\u003e(0.020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.548***\u003c/p\u003e\u003cp\u003e(0.017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.240***\u003c/p\u003e\u003cp\u003e(0.037)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.406***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.083***\u003c/p\u003e\u003cp\u003e(0.031)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.240***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.420***\u003c/p\u003e\u003cp\u003e(0.077)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.905***\u003c/p\u003e\u003cp\u003e(0.052)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elnincome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003cp\u003e(0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.030***\u003c/p\u003e\u003cp\u003e(0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.026***\u003c/p\u003e\u003cp\u003e(0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.023***\u003c/p\u003e\u003cp\u003e(0.002)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational Prestige\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.002***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.004***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.006***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.087***\u003c/p\u003e\u003cp\u003e(0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.095***\u003c/p\u003e\u003cp\u003e(0.014)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.057***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.028***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.000***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEastern Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003cp\u003e(0.018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.044***\u003c/p\u003e\u003cp\u003e(0.016)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.094***\u003c/p\u003e\u003cp\u003e(0.020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.083***\u003c/p\u003e\u003cp\u003e(0.018)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHas Partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.135***\u003c/p\u003e\u003cp\u003e(0.021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.338***\u003c/p\u003e\u003cp\u003e(0.024)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReligious Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003cp\u003e(0.122)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.224\u003c/p\u003e\u003cp\u003e(0.293)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.334**\u003c/p\u003e\u003cp\u003e(0.162)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.090***\u003c/p\u003e\u003cp\u003e(0.092)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003econs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.928***\u003c/p\u003e\u003cp\u003e(0.022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.607***\u003c/p\u003e\u003cp\u003e(0.018)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.770***\u003c/p\u003e\u003cp\u003e(0.085)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.841***\u003c/p\u003e\u003cp\u003e(0.080)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Robust standard errors are reported in parentheses. p\u0026thinsp;\u0026lt;\u0026thinsp;0.10, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a forest plot of coefficients from the Conditional Mixed Process (CMP) robustness check. Through different colored dots and confidence intervals, the figure clearly illustrates the robustness of variable coefficients across the four equations. Compared with GSEM results, the CMP model coefficient estimates maintain high consistency in terms of directionality and significance, further validating the reliability of the research findings. Particularly noteworthy is that the differential effect patterns of education variables across equations are consistently confirmed in both analytical approaches, enhancing our confidence in the mechanisms through which socioeconomic status operates.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e employs a correlation coefficient heatmap to display the correlational relationships among residuals of the four GSEM models. The heatmap uses color intensity to represent correlation strength, with deep red indicating strong positive correlation and deep blue indicating strong negative correlation. The figure reveals strong positive correlations between Model 2 (physical activity) and Model 3 (subjective health) and Model 4 (subjective well-being) (0.63 and 0.96, respectively), reflecting the close connection between physical activity and health well-being. Conversely, Model 1 (religious participation) generally shows negative correlations with other models, consistent with our findings regarding the limited role of religious participation in the Chinese cultural context.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrates the nonlinear effects of age on subjective health and subjective happiness. The blue line represents the impact of age on subjective health, showing a continuous declining trend that reflects the gradual deterioration of physiological functions with aging. The orange line represents the impact of age on subjective happiness, displaying the classic U-shaped curve where happiness levels are relatively high in youth and old age but reach their lowest point in middle age. This finding is highly consistent with the famous \"happiness U-curve\" phenomenon in international research, revealing the complex patterns of happiness changes throughout the life course.\u003c/p\u003e\u003cp\u003eTo illustrate how including control variables and regional factors affects model fit and coefficient estimates, Tables 5, 6, and 7 present the results of three nested GSEM (Generalized Structural Equation Modeling) models. These models estimate coefficients across four equations: religious participation (react), physical activity (tycy), subjective health (srh), and subjective well-being (swb). Table 5 includes only socioeconomic status indicators—educational attainment (xueli3), logarithmic income (lnincome), and occupational prestige (siops)—along with the mediating variables. Table 6 builds upon this by incorporating demographic characteristics such as gender, age, and marital status. Table 7 further extends the model by including geographic regions (Eastern and Central), thereby allowing for an assessment of regional heterogeneity.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e primarily captures the direct effects of education, income, and occupational prestige on religious participation and physical activity. Education exhibits consistently high and statistically significant coefficients in the subjective health and well-being equations. At the same time, income and occupational prestige display positive and negative associations with health and happiness, respectively.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e demonstrates that, with the inclusion of demographic variables, the direction and significance of most core variables remain largely consistent with those in the baseline model, though some coefficient magnitudes change slightly. The coefficient for being female is positive in the religious participation equation, negative in the health equation, and positive in the happiness equation, indicating that gender exerts heterogeneous effects on both mediators and outcome variables.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, which presents the final model specification, reveals that individuals in Eastern and Central regions show significantly positive coefficients in religious participation and physical activity equations relative to those in Western regions. This finding suggests that regional differences in economic and cultural context positively influence individuals\u0026rsquo; engagement in religious and exercise behaviors. The effects of regional variables on health and happiness are also differentiated, pointing to region-specific mechanisms in shaping individual well-being.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNested GSEM (SES Only)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003eReact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003eTycy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003eSrh\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 4\u003c/p\u003e\u003cp\u003eSwb\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior High School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.270***\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.885***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.619***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.212***\u003c/p\u003e\u003cp\u003e(0.031)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.172***\u003c/p\u003e\u003cp\u003e(0.056)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.086***\u003c/p\u003e\u003cp\u003e(0.052)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.189***\u003c/p\u003e\u003cp\u003e(0.048)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.455***\u003c/p\u003e\u003cp\u003e(0.055)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elnincome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.052***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.033***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.012***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational Prestige\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.003***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.005***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.005***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001**\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReligious Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.047\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003cp\u003e(0.039)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.311***\u003c/p\u003e\u003cp\u003e(0.026)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.305***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e_cons\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.584***\u003c/p\u003e\u003cp\u003e(0.042)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.905***\u003c/p\u003e\u003cp\u003e(0.033)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.522***\u003c/p\u003e\u003cp\u003e(0.033)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.761***\u003c/p\u003e\u003cp\u003e(0.037)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Model 1 includes only the variables xueli3 (educational attainment), lnincome (logarithmic income), and siops (occupational prestige), along with the corresponding structural equations among the dependent variables.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNested GSEM (SES\u0026thinsp;+\u0026thinsp;Demographics)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVarible\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003eReact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003eTycy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003eSrh\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 4\u003c/p\u003e\u003cp\u003eSwb\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior High School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.251***\u003c/p\u003e \u003cp\u003e(0.038)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.893***\u003c/p\u003e\u003cp\u003e(0.028)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.201***\u003c/p\u003e\u003cp\u003e(0.029)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.322***\u003c/p\u003e\u003cp\u003e(0.033)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.195***\u003c/p\u003e \u003cp\u003e(0.063)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.072***\u003c/p\u003e\u003cp\u003e(0.056)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.325***\u003c/p\u003e\u003cp\u003e(0.053)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.667***\u003c/p\u003e\u003cp\u003e(0.060)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elnincome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.007*\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.056***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.035***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.020***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational Prestige\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.002***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.00457***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.002***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001**\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.347***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.151***\u003c/p\u003e\u003cp\u003e(0.026)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.161***\u003c/p\u003e\u003cp\u003e(0.026)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.206***\u003c/p\u003e\u003cp\u003e(0.029)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.002\u003c/p\u003e\u003cp\u003e(0.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e(0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.099***\u003c/p\u003e \u003cp\u003e(0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.06344***\u003c/p\u003e \u003cp\u003e(0.00593)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.000\u003c/p\u003e \u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHas Partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003cp\u003e(0.044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.233***\u003c/p\u003e\u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.746***\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReligious Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.048\u003c/p\u003e\u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003cp\u003e(0.039)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.338***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.310***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e_cons\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.719***\u003c/p\u003e \u003cp\u003e(0.1626)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.973***\u003c/p\u003e \u003cp\u003e(0.124)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.003***\u003c/p\u003e\u003cp\u003e(0.141)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.089***\u003c/p\u003e\u003cp\u003e(0.143)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Model 2 builds upon Model 1 by adding control variables for gender, age, age squared, and marital status (Has Partner), in addition to the socioeconomic indicators and structural paths.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNested GSEM (SES\u0026thinsp;+\u0026thinsp;Demographics\u0026thinsp;+\u0026thinsp;Region)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModel 1\u003c/p\u003e\u003cp\u003eReact\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel 2\u003c/p\u003e\u003cp\u003eTycy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModel 3\u003c/p\u003e\u003cp\u003eSrh\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eModel 4\u003c/p\u003e\u003cp\u003eSwb\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJunior High School\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.259***\u003c/p\u003e \u003cp\u003e(0.039)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.857***\u003c/p\u003e\u003cp\u003e(0.029)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.202***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.314***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollege and Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.206***\u003c/p\u003e \u003cp\u003e(0.064)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.997***\u003c/p\u003e\u003cp\u003e(0.057)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.331***\u003c/p\u003e\u003cp\u003e(0.054)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.654***\u003c/p\u003e\u003cp\u003e(0.062)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elnincome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.008*\u003c/p\u003e\u003cp\u003e(0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.055***\u003c/p\u003e\u003cp\u003e(0.003)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.036***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.020***\u003c/p\u003e\u003cp\u003e(0.004)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational Prestige\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.003***\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.005***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.002***\u003c/p\u003e \u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.002**\u003c/p\u003e\u003cp\u003e(0.001)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.345***\u003c/p\u003e\u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.137***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.161***\u003c/p\u003e \u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.203***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.003\u003c/p\u003e \u003cp\u003e(0.007)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003cp\u003e(0.005)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.099***\u003c/p\u003e \u003cp\u003e(0.006)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.064***\u003c/p\u003e \u003cp\u003e(0.006)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eage\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.000\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001***\u003c/p\u003e\u003cp\u003e(0.000)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEastern Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.064\u003c/p\u003e\u003cp\u003e(0.044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.059*\u003c/p\u003e \u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.230***\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.742***\u003c/p\u003e\u003cp\u003e(0.036)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCentral Region\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1185***\u003c/p\u003e\u003cp\u003e(0.040)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.312***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003cp\u003e(0.031)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.088***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHas Partner\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.321***\u003c/p\u003e\u003cp\u003e(0.044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.149***\u003c/p\u003e\u003cp\u003e(0.034)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1644***\u003c/p\u003e\u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.176***\u003c/p\u003e\u003cp\u003e(0.039)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReligious Participation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003cp\u003e(0.035)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.003\u003c/p\u003e\u003cp\u003e(0.039)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhysical activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.338***\u003c/p\u003e\u003cp\u003e(0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.306***\u003c/p\u003e\u003cp\u003e(0.030)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e_cons\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.8415***\u003c/p\u003e \u003cp\u003e(0.1642)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.079***\u003c/p\u003e \u003cp\u003e(0.125)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.952***\u003c/p\u003e\u003cp\u003e(0.142)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.026***\u003c/p\u003e\u003cp\u003e(0.144)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27,889\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: Model 3 extends Model 2 by incorporating geographic region dummy variables to account for regional heterogeneity.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e compares the coefficient magnitudes of variables across three nested GSEM models through horizontal bar charts. The figure clearly illustrates the changing trends of core variable coefficients as control variables are progressively introduced. The figure shows that education variables (middle school and college \u0026amp; above) maintain relatively stable effect patterns across different models, indicating that the influence of education on health and happiness demonstrates strong robustness. Meanwhile, the inclusion of control variables such as marital status and regional differences reveals the complexity of socioeconomic status influence mechanisms, providing more detailed empirical evidence for understanding health inequality in the Chinese social context.\u003c/p\u003e\u003cp\u003eFigure 8 employs smoothed line charts to display the coefficient change trajectories of four core socioeconomic status indicators across three nested models. The figure clearly shows that as demographic and regional variables are progressively controlled, each SES indicator exhibits different stability patterns. The coefficients for middle school and college \u0026 above education remain relatively stable across models, demonstrating the robustness of education effects; the coefficient for income (log) shows slight fluctuations but maintains overall consistent trends; occupational prestige coefficients remain relatively stable and close to the zero-effect line, which aligns with the complexity of occupational prestige effects we found in the main analysis. This progressive modeling approach effectively validates the robustness of the research findings.\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cp\u003eThe results of this study indicate that socioeconomic status (SES)\u0026mdash;measured by educational attainment, income, and occupational prestige\u0026mdash;has a statistically significant impact on subjective health and well-being through both direct effects and specific lifestyle mediators. Educational attainment plays a notable role in promoting individuals' perceived health and happiness. Research has shown that education directly improves health awareness and literacy, making individuals more likely to engage in positive health behaviors such as regular checkups, balanced diets, and cautious medication use\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. Moreover, education indirectly enhances quality of life and subjective well-being through increasing income and social capital. In the Chinese context, studies have found a stable positive correlation between moderate-to-high educational attainment and higher happiness among migrants, urban workers, and university graduates\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e. The benefits of education extend beyond the economic level to social networks and modes of thinking, serving as buffers or protective factors for health and happiness\u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIncome is another core dimension through which SES influences health and happiness. Higher income typically implies more abundant material conditions and a greater ability to cope with life risks, significantly improving life satisfaction\u003csup\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e. However, once income reaches a certain level, its marginal utility for subjective well-being declines\u0026mdash;a phenomenon known as the \"Easterlin Paradox\"\u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e. Many researchers emphasize the nonlinear effects of income: while income growth may bring substantial improvements for low- and middle-income groups, the happiness of high-income individuals tends to depend more on social recognition, job satisfaction, and spiritual pursuits\u003csup\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e. This pattern has been partially validated in Chinese studies, where individuals with better economic conditions generally report better health, but their happiness does not necessarily increase if burdened by growing social pressures\u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOccupational prestige is often regarded as a core symbol of social status, influencing how individuals are respected in workplace and social interactions, indirectly affecting their self-esteem, sense of self-worth, and social identity\u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e. Existing research indicates that people in high-prestige occupations report higher happiness levels\u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. However, the effects of occupational prestige may be attenuated when variables such as education and income are controlled\u003csup\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/sup\u003e. Furthermore, when social or self-expectations become overly focused on external prestige, individuals may experience increased stress and responsibility, ultimately diminishing their happiness\u003csup\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThis study examines the mediating roles of physical activity and religious participation in the relationship between SES and subjective health and happiness. Physical activity plays a significant positive mediating role. Individuals with higher SES\u0026mdash;particularly those with more education\u0026mdash;are more likely to engage in regular physical activity\u003csup\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e. Those with higher education and income tend to have stronger health awareness and greater resources to invest in exercise, while individuals with higher social status often enjoy more leisure time and access to better fitness facilities\u003csup\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e. These SES-based differences in exercise participation ultimately shape health and happiness outcomes\u003csup\u003e[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e. The study finds that higher frequency and consistency of physical activity are associated with better subjective health and higher happiness levels. Exercise enhances physical and mental health, reduces illness risk, alleviates negative emotions such as anxiety and depression, and provides opportunities for social interaction and emotional uplift\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn contrast, religious participation demonstrates a more complex and less robust mediating role. Overall, this study finds that religious activity does not significantly affect subjective well-being and has a limited impact on subjective health. Frequent religious participation is not associated with higher happiness or better health outcomes in this context. This finding may appear inconsistent with Western literature, which emphasizes religion's positive role in providing emotional support, social connections, and meaning\u003csup\u003e[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/sup\u003e. However, this study aligns with existing findings describing the contingent relationship between religion and well-being in the Chinese context\u003csup\u003e[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]\u003c/sup\u003e. Chinese religious beliefs differ markedly from Western societies, exhibiting deinstitutionalization, ritualism, and localization characteristics\u003csup\u003e[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]\u003c/sup\u003e. China follows a secular state model where religious belief is essentially personal choice and overall religiosity remains low\u003csup\u003e[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]\u003c/sup\u003e. Many individuals may only turn to religion during life crises rather than being regular practitioners\u003csup\u003e[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]\u003c/sup\u003e. \"Religious participation without strong belief\" is common in China, where people participate in religious ceremonies primarily out of custom or social obligation rather than genuine spiritual conviction\u003csup\u003e[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]\u003c/sup\u003e. Under these conditions, religious activities may not produce significant psychological benefits. Additionally, many religious participants belong to socially disadvantaged groups where spiritual solace cannot compensate for structural hardships such as poverty or poor health\u003csup\u003e[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eControl variables reveal meaningful patterns. Gender differences show females reporting lower subjective health but higher happiness levels, reflecting women's greater health awareness and stronger social support networks\u003csup\u003e[\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]\u003c/sup\u003e. This gender paradox in well-being has been documented across multiple cultures, where women consistently report more negative affect but similar or higher levels of life satisfaction compared to men\u003csup\u003e[\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]\u003c/sup\u003e. Age shows expected associations with both outcomes: subjective health evaluations decline with age due to physiological deterioration, while the relationship with happiness is more complex, suggesting psychological adaptation mechanisms\u003csup\u003e[\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]\u003c/sup\u003e. Geographic region significantly influences health and well-being, with residents in economically developed areas generally reporting better subjective health due to superior healthcare resources and living conditions\u003csup\u003e[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]\u003c/sup\u003e. However, rapid urban development stress may partially offset happiness gains.\u003c/p\u003e\u003cp\u003eDespite its contributions, the study has several limitations. The cross-sectional design limits causal inference capabilities, as reverse causality or omitted variable bias cannot be entirely excluded despite theoretical grounding and comprehensive covariate adjustment. Subjective health and happiness are self-reported indicators susceptible to individual interpretation and cultural norms. SES indicators have constraints\u0026mdash;educational attainment cannot capture quality variations, income measures may omit assets and social benefits, and occupational prestige perceptions may vary across generations and regions. Additionally, specific marginalized populations may remain underrepresented, potentially affecting external validity.\u003c/p\u003e\u003cp\u003eThese findings have important implications for China's \"Healthy China 2030\" strategy. The strong mediating role of physical activity suggests that improving exercise accessibility across socioeconomic strata could effectively reduce health disparities. Public health policies should prioritize improving access to physical activity opportunities while recognizing the limited role of religious engagement in promoting population well-being in secular societies. These findings suggest that researchers should incorporate \"lifestyle\" as a meso-level factor when analyzing social stratification. Given significant differences between Western and Chinese traditions regarding religion and physical activity, localized research perspectives are crucial for accurately interpreting how Chinese people construct meanings of \"health\" and \"happiness\" during social change.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study reveals that socioeconomic status appears to shape subjective health and well-being among Chinese adults through a coupling mechanism of structure, behaviour, and outcome, with physical activity serving as an important mediating pathway in these relationships within the constraints of cross-sectional data. In contrast to Western research findings, religious participation exhibits different patterns of influence on health and happiness within China's secular cultural context, though this finding is limited by the behavioral measurement of religious participation rather than intrinsic religiosity. These conclusions should be interpreted cautiously given the study's cross-sectional design, specific sample characteristics, and cultural context, and may not generalize to other populations or time periods.These findings underscore the importance of understanding the coupling dynamics between social structure and individual outcomes, and highlight the need for culturally sensitive physical activity interventions tailored to different socioeconomic groups.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This work was supported by the National Social Science Foundation of China [24BTY085] under the project \u0026quot;Research on the Integrated Construction of Smart Sports in Chinese Universities.\u0026quot;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study utilized publicly available secondary data from the China General Social Survey (CGSS), which has received ethics approval from the Renmin University of China Ethics Committee. All CGSS participants provided informed consent. No additional ethics approval was required for this secondary data analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe datasets used in this study, specifically the 2015, 2017, and 2018 waves of the Chinese General Social Survey (CGSS), are publicly available for free download after simple registration on the official website of the Chinese National Survey Data Archive (CNSDA) at: \u003cstrong\u003ehttp://cnsda.ruc.edu.cn/\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX.L. and G.Z. contributed equally as co-first authors to conceptualization, data collection and analysis, methodology development, and original draft writing. R.L. contributed to conceptualization and methodology, provided supervision and project administration. All authors reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLi Y, Guo Y, Liu J (2021) Income-related health inequality among Chinese adults during the COVID-19 pandemic: evidence based on an online survey. Int J Equity Health 20(1):88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12939-021-01448-9\u003c/span\u003e\u003cspan address=\"10.1186/s12939-021-01448-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSong Q, Smith JP, Kancherla V (2021) Area-level socioeconomic inequalities in mortality in China: a nationwide cohort study based on the ChinaHEART project. 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J Mental Health Clin Psychol 4(2):8\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.29245/2578-2959/2020/2.1196\u003c/span\u003e\u003cspan address=\"10.29245/2578-2959/2020/2.1196\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"socioeconomic status, physical activity, religious participation, subjective health, well-being, structural equation modeling, China","lastPublishedDoi":"10.21203/rs.3.rs-7577961/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7577961/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eChina's rapid socio-economic transformation has intensified social stratification and resource inequality, creating disparities in health outcomes and subjective well-being across different socioeconomic strata. While existing research has established the association between socioeconomic status (SES) and health outcomes, the behavioral mechanisms through which SES influences subjective health and happiness remain underexplored, particularly in the Chinese cultural context where physical activity and religious participation exhibit unique characteristics.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study utilized nationally representative survey data from the Chinese General Social Survey (CGSS) and employed Generalized Structural Equation Modeling (GSEM) to examine the relationships among SES indicators (educational attainment, income, occupational prestige), lifestyle mediators (physical activity and religious participation), and outcome variables (subjective health and well-being). Conditional Mixed Process (CMP) Probit regression was conducted as a robustness check. The analysis controlled for demographic variables including gender, age, marital status, and regional factors.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eEducational attainment demonstrated the strongest positive associations with both subjective health and well-being, with college-educated individuals showing total associations of 1.046 for health and 1.294 for well-being. Physical activity emerged as a significant positive mediator, accounting for 60.9% and 46.4% of the total associations of junior high education with health and happiness, respectively. However, given the cross-sectional nature of this study, these findings represent associations rather than causal effects.For individuals with higher education, the mediation proportions reached 68.4% and 49.5%. Income showed consistent positive associations with both outcomes, with mediation effects of 32.9% for health and 44.5% for well-being. Occupational prestige exhibited complex patterns with mixed effects across equations. Contrary to Western findings, religious participation showed no significant positive effects on subjective health or well-being, reflecting the unique secular context of contemporary China. Gender differences revealed that females reported lower subjective health but higher happiness levels. Regional variations indicated that residents in Eastern and Central regions demonstrated different patterns of religious and physical activity participation compared to Western regions.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe study confirms that SES significantly influences subjective health and well-being through both direct pathways and behavioral mediators, with physical activity serving as a crucial transmission mechanism while religious participation lacks significant mediating effects in the Chinese context. These findings suggest that public health policies should prioritize improving access to physical activity opportunities across different socioeconomic strata while recognizing the limited role of religious engagement in promoting population well-being in secular societies.\u003c/p\u003e","manuscriptTitle":"Behavioral Bridges to Health and Well-being: How Physical Activity Precedes Religious Participation in Mediating the Effects of Socioeconomic Status","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-25 15:13:11","doi":"10.21203/rs.3.rs-7577961/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-12T15:23:21+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T08:22:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T03:46:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276793042766792928896527631696056605970","date":"2026-01-23T15:57:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"18965944028050375835559247738653553398","date":"2026-01-05T03:03:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-11-14T09:23:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-14T07:44:58+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-04T13:35:02+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-20T14:49:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Humanities and Social Sciences Communications","date":"2025-10-20T14:45:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"humanities-and-social-sciences-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"palcomms","sideBox":"Learn more about [Humanities \u0026 Social Sciences Communications](http://www.nature.com/palcomms/)","snPcode":"41599","submissionUrl":"https://submission.springernature.com/new-submission/41599/3","title":"Humanities and Social Sciences Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"14c8a6e4-045b-4e7b-8d6e-bec6acdc5979","owner":[],"postedDate":"November 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":58493044,"name":"Social science/Anthropology"},{"id":58493045,"name":"Health sciences/Health care"},{"id":58493046,"name":"Humanities/Health humanities"},{"id":58493047,"name":"Biological sciences/Psychology"},{"id":58493048,"name":"Social science/Psychology"},{"id":58493049,"name":"Social science/Social policy"},{"id":58493050,"name":"Social science/Sociology"}],"tags":[],"updatedAt":"2026-05-17T06:08:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-25 15:13:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7577961","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7577961","identity":"rs-7577961","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}