Research on the Impact Mechanism of Offspring Human Capital Endowment on the Health-Related Quality of Life of Rural Fathers from the Perspective of Digital Integration

Research on the Impact Mechanism of Offspring Human Capital Endowment on the Health-Related Quality of Life of Rural Fathers from the Perspective of Digital Integration | 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 Research Article Research on the Impact Mechanism of Offspring Human Capital Endowment on the Health-Related Quality of Life of Rural Fathers from the Perspective of Digital Integration Changli Jia, Panpan Ren, Jingjing Jia, Jinglin Xu, Mengyao Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6299719/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: China's rural population is aging and facing challenges in geriatric health management. Under the family-centered health promotion model, existing studies have mostly focused on the unidirectional health impact of the father's generation on the children's generation and the role of education and single human capital, neglecting the feedback mechanism of the children's multidimensional human capital (education and health) on the health of the father's generation. Based on the family system theory and field research data, this study systematically analyzes the role of offspring human capital on the quality of life in old age, and provides a scientific basis for the development of intergenerational health support policies. Methods: Using field survey data collected from Chongqing, Gansu, and Zhejiang between July and August 2023, the study employs linear regression to analyze the relationship between offspring human capital and parental HRQoL. The mediating role of perceived social support is tested via the bootstrap method, and the moderating role of digital health literacy is analyzed using moderation regression. Results: The average parental health utility value (0.90±0.18) is lower than that of off-spring (0.97±0.09), indicating generally good health among respondents. Offspring educational human capital exhibits an inverted U-shaped relationship with parental HRQoL, while offspring health human capital is positively correlated (β=0.3560, p<0.001). Perceived social support mediates this relationship (β=0.0085, p<0.001), ac-counting for 10.89% and 6.78% of the effect. Digital health literacy negatively moderates the relationship between offspring health human capital and parental HRQoL, but no significant moderation was found in the relationship with offspring educational human capital. Conclusion: Offspring human capital positively influences parental HRQoL, with the effect of health human capital outweighing that of education. Perceived social support serves as a mediator, and digital health literacy moderates the impact of offspring health human capital on parental HRQoL. 1. Background Population aging has become a significant global issue in terms of both healthcare and social demographics. According to the World Health Organization, China is one of the countries with the fastest aging population growth. By 2040, it is expected that the proportion of people aged 60 and above in China will reach 28% [ 1 ] . By the end of 2024, there will be 310.31 million elderly people aged 60 and above in China, exceeding 300 million for the first time; the population aged 65 and above will be 220.23 million, accounting for 15.6% of the total [ 2 ] . In addition, due to the gap between urban and rural economic and social development and the impact of population migration, the age structure of China's population is characterized by significant urban-rural differences, and the trend of population aging in rural areas is bound to be more severe. According to life course theory, elderly individuals in the later stages of life are more likely to experience health problems, particularly with a significant increase in the prevalence of chronic diseases, which can place a heavy burden on social, economic, and healthcare systems. In this context, exploring intergenerational health support mechanisms is crucial for improving the quality of life for elderly individuals in rural areas. Research indicates that human capital plays an increasingly important role in improving individual health outcomes [ 3 ] , with a significant positive correlation between higher education levels and longer life expectancy, while lower education levels negatively impact life expectancy [ 4 ] . Family Systems Theory further emphasizes that the family is an interactive whole, where the emotions, behaviors, and health responses of family members influence each other [ 5 ] . A large body of research has focused on the impact of parents on children's health, particularly how parental health behaviors significantly affect children's physical and mental health [ 6 , 7 ] . However, intergenerational interaction involves not only the influence of parents on children's health but also the impact of offspring on parental health, which has long been neglected in academic literature. Despite the release of the "14th Five-Year Plan for Healthy Aging" by the National Health Commission of the People's Republic of China in 2022, emphasizing that "the family is the first line of defense for health" and further highlighting the key role of family involvement in maintaining the health of elderly individuals [ 8 ] , existing research still faces three major limitations: First, much of the focus remains on the role of education as a unidimensional human capital factor, overlooking the synergistic effects of health as a core dimension of human capital; second, there is an overemphasis on the unidirectional influence of parents on offspring, with a lack of systematic exploration of the pathways through which offspring human capital can benefit parental health; third, there is insufficient analysis of the multidimensional nature of family support mechanisms (economic, emotional, informational) and the moderating effects of technology in the digital age. To address the aforementioned gaps, this study constructs an analytical framework based on Family Systems Theory, focusing on the differentiated impact of offspring's “education-health” dual-dimensional human capital on the health and quality of life of rural parents. Previous research on human capital and health has shown that human capital investment has a positive impact on population health, with individuals possessing higher levels of human capital—especially those with higher education—typically demonstrating better cognitive abilities regarding their health behaviors [ 9 , 10 ] . Research indicates that the level of human capital investment in offspring is a key factor influencing the health disparities of elderly parents [ 11 ] , with offspring's education level significantly affecting parental health behaviors, promoting smoking cessation, and improving overall health conditions [ 12 , 13 ] . However, some studies have also found an inverted U-shaped relationship between years of education and family health, suggesting that rural residents derive limited health benefits from higher education, and the health returns for highly educated individuals tend to diminish over time [ 14 ] . Nonetheless, overall, offspring education still positively impacts the health quality of rural parents, although this effect weakens over time. Most studies have primarily examined human capital from the single dimension of education, while neglecting the health dimension [ 15 , 16 ] . Some scholars have recognized that both education and health are core factors influencing quality of life [ 17 , 18 ] . With declining fertility rates and increasing aging, health as an important component of human capital has attracted growing attention from researchers. For example, some studies have explored the impact of health human capital on positive emotions, happiness, and the tendency toward elder abuse [ 19 , 20 ] . Individuals with strong health human capital typically exhibit higher levels of happiness and life satisfaction, thus maintaining a higher quality of life. This study aims to fill this gap by exploring how the human capital of the younger generation, through education and health, influences the health and quality of life of the older generation. Through the above analysis, it can be observed that offspring with higher education levels are better able to provide various health resources for their parents, including more health knowledge, health information, and health behaviors, all of which have a positive impact on parental health [ 21 ] . However, due to the constraints of the urban-rural dual household registration system, as the education level of rural offspring increases, the likelihood of separation between offspring and parents also increases. In such cases, parents often face significant life pressures, including daily labor and economic stress, which in turn affect their health improvement. Thus, we propose the following hypothesis H1a: There is an inverted U-shaped relationship between offspring education level and rural parental health quality of life. That is, as the education level of offspring increases, parental health quality of life first improves and then stabilizes. Additionally, from the perspective of intergenerational transmission, when offspring possess high levels of health human capital, they typically gain more economic resources, income, and opportunities, leading to higher socioeconomic status. In the unique context of China, this also leads to reciprocal support for parents, alleviating their retirement and living pressures, thereby improving parental health quality of life. Hence, we propose the following hypothesis H1b: There is a positive correlation between offspring health status and parental health quality of life. That is, offspring health status typically influences parental health by directly providing health knowledge and resources. Furthermore, human capital not only directly affects health but can also improve individual health through various potential mechanisms [ 22 ] . Existing research indicates that human capital can enhance public health through economic support, social capital, and living arrangements [ 23 – 25 ] . With the development of positive psychology, the impact of perceived social support on individual health outcomes has become increasingly profound. The more social support individuals receive from family, friends, and significant others, the less likely they are to experience negative mental health issues such as depression and anxiety [ 26 ] . The social support buffering model suggests that perceived social support provides psychological energy, helps regulate negative emotions, and facilitates access to social resources [ 27 ] . This buffering effect manifests in several forms: First, economic support, where offspring's support for their parents can be seen as an increase in individual income, providing financial assistance to improve parents' quality of life [ 28 , 29 ] ; second, emotional support, where strong family relationships affect offspring's willingness to provide emotional care for their parents. The closer the parent-child relationship, the more likely offspring are to engage in reciprocal behaviors, promoting mutual concern for each other's health and encouraging healthy behaviors [ 30 ] ; third, informational support, where offspring assist their parents in accessing online health information, fostering a "bottom-up" model of intergenerational interaction that influences parents' self-awareness and health consciousness [ 31 ] . The above literature suggests that offspring human capital is closely related to parental perceived social support. Offspring with higher human capital are able to provide more social support to their elderly parents, including economic, emotional, and informational support, thereby enhancing the social support that parents perceive and helping them cope with negative life events. In contrast, offspring with lower human capital often leads to less perceived social support for their parents, which in turn affects their health. Based on this, we propose the following hypothesis H2: Perceived social support mediates the relationship between offspring human capital (education and health) and parental health quality of life. Furthermore, digital health literacy is the combination of digital literacy and health literacy, referring to an individual's ability to access information through digital devices and apply this information to solve health-related issues [ 32 ] . With the development of the internet and information and communication technologies, digitalization has become a mainstream trend in societal development, with digital media gradually becoming the preferred source for individuals seeking health information [ 33 ] . From the perspective of health management, the ability to access online health information plays a crucial role in helping individuals independently understand disease symptoms, the pros and cons of medical treatments, and improving public health management and decision-making capabilities [ 34 ] . Previous studies have highlighted the importance of improving digital health literacy in promoting positive aging [ 35 ] , noting that internet use can protect the cognitive function of elderly individuals and improve their health [ 36 ] . It can thus be concluded that accessing and utilizing digital health information is a key tool for improving healthy aging. It is a critical factor enabling middle-aged and elderly individuals to benefit from the digitalization of healthcare services, directly influencing their future health quality of life. Therefore, considering that the digital health literacy of parents may affect their ability to utilize health information provided by their offspring, this study explores how digital health literacy moderates the impact of offspring human capital on parental health quality of life. Traditionally, health information transmission has been viewed as flowing from parents to children, with health knowledge and information being passed down. However, for older rural individuals who have limited internet skills and health information-seeking abilities, younger offspring with more abundant human capital resources and stronger digital technology skills may be better positioned to provide health information. Parents with strong digital health literacy are more likely to benefit from these resources, thereby improving their quality of life. Thus, we propose the following hypothesis H3: Digital health literacy moderates the relationship between offspring human capital and parental health quality of life. 2. Materials and Methods 2.1 Study design, setting, and participants The data used in this study were collected through field research conducted by our research team in the provinces of Zhejiang, Chongqing, and Gansu from July to August 2023. The survey employed a stratified random sampling method. In each province (or city), two counties (or districts) were randomly selected based on their economic development levels. For each selected county (or district), two towns were randomly chosen, and for each town, two administrative villages were randomly selected, resulting in a total of 24 villages. The survey was conducted using a household approach to cluster sampling within the selected villages. A total of 2,000 questionnaires were distributed, and 1,860 were returned, resulting in a response rate of 93%. The survey included 3,308 participants, indicating good data collection effectiveness. Since this study aims to investigate the health relationships between the younger and older generations, we excluded empty-nest families and dual-income-no-kids (DINK) families during the sample selection process. Consequently, a total of 345 families were included in the statistical analysis. The inclusion criteria were as follows: the basic unit of the survey was the family, which included the older generation and their cohabiting children; the age of the younger generation was ≥ 18 years; and they had been residing at home for at least six months during the survey. After excluding missing values for various variables, a final matched sample of 759 pairs of younger and older generations was included in the statistical analysis. 2.2. Study variables 2.2.1. The Dependent Variable Health-related quality of life will be measured using the European Five Dimensions Health Scale (EQ-5D-3L). It evaluates health-related quality of life across five dimensions: mobility (MO), self-care (SC), usual activities (UA), pain/discomfort (PD), and anxiety/depression (AD). Respondents assess their health status in each dimension by selecting one of three levels: no problems, mild problems, or severe problems. These responses are then converted into a health utility value (U) using a utility scoring system. In this study, The health utility values (U) for the target population will be calculated using the conversion table developed by Liu et al [ 37 ] . The calculation of the health utility values is performed using the formula: U = 1-(MO n +SC n +UA n +PD n +AD n ), n = 1,2,3,4,5 The health utility value ranges from − 0.391 to 1.000, with higher scores indicating better health status. 2.2.2. The Independent Variable In this study, the concept of human capital for offspring is represented by two proxy variables: health human capital and educational human capital. Specifically, health human capital is measured using the average health utility value of the offspring, while educational human capital is assessed based on the average years of education of the offspring. The health utility value of offspring is derived from the EQ-5D-3L scores of all surveyed offspring. In contrast, the average health utility value of offspring refers to the mean health utility value across all offspring in the study sample, serving as an indicator of the overall health status of the offspring population. 2.2.3. Mediating Variable Social support will be measured using the Perceived Social Support Scale (PSSS-SF3), developed by MH Zimet et al. in 1987, and translated for use by Chinese scholar Jiang Qianjin. This scale comprises three dimensions, including emotional support, informational support, and tangible support that individuals can receive from family, friends, or other social networks. All measurement items utilize a 7-point Likert scale, where higher scores indicate a stronger perception of social support from external sources by the parents. In this study, social support was measured based on responses from parents, rather than their offspring. The aim was to assess the subjective perception of support that rural elderly parents receive from their children, including emotional support, informational support, and tangible support. All questionnaire items were directly answered by the parents to ensure that the data accurately reflect their genuine perceptions. 2.2.4. Moderating Variable Digital health literacy has often been measured using instruments such as the eHealth Literacy Scale (eHEALS) [ 38 ] and the Digital Health Literacy Instrument (DHLI) [ 39 ] . Additionally, scholars in China have developed a community-based digital health literacy assessment scale tailored to the characteristics of older adults, which includes three dimensions: the ability to access and assess digital health information, interaction capabilities, and application skills [ 40 ] . Due to limitations in the content of the questionnaire survey, referring to existing research [ 41 ] ,this study primarily assesses the digital health information acquisition level of elderly parents in rural areas by asking them whether they have used digital media to access health-related information. This single-item measure serves as an indicator of their engagement with digital health resources. 2.2.5. Control Variable Family structure is a crucial determinant of family social capital [ 42 ] . Different structural forms of families exhibit variations in resource allocation and functional realization, which, in turn, affect the human capital of the offspring [ 43 ] . Research indicates that family structure profoundly influences individual physical health and psychological development [ 44 , 45 ] . Additionally, family type plays a significant role in the health behaviors of offspring [ 46 , 47 ] .Therefore, drawing from prior studies, this research selects individual demographic characteristics, health behaviors, and family characteristics as control variables. Specifically, individual demographic characteristics include age, gender, educational attainment, and employment status; health behaviors encompass smoking, alcohol consumption, and physical exercise; while family characteristics consist of the offspring's age, gender, family power structure, and family type. 2.3. Data Analysis To analyze the impact of offspring human capital on parental health-related quality of life, this study establishes the following regression model: $$\:{pheal}_{i}={c}_{0}+{c}_{1}{edu}_{i}+{c}_{2}{heal}_{i}+\sum\:{c}_{3}{x}_{i}+{{\epsilon\:}_{1}}_{i}$$ In this model, \(\:{\:pheal}_{i}\) represents the health utility value of the parent. \(\:{edu}_{i}\:\) denotes the educational human capital of the offspring. \(\:{heal}_{i}\:\) indicates the health human capital of the offspring. \(\:{x}_{i}\:\) includes the control variables. \(\:{c}_{0}\:\) is the constant term. \(\:{c}_{1}\) 、 \(\:{c}_{2}\) 、 \(\:{c}_{3}\) are the coefficients to be estimated. \(\:{{\epsilon\:}_{1}}_{i}\:\) represents the random disturbance term. In this study, the data collected were double-checked using EpiData software to ensure data entry quality. During the statistical analysis phase, R version 4.2.3 was used for data analysis. Descriptive statistics were employed to describe the basic demographic characteristics. Multiple linear regression was used to analyze the influencing factors. The bootstrap method was applied to identify mediation effects, and moderation analysis was conducted to examine the moderating role of digital health literacy. A p-value of < 0.05 was considered statistically significant. 3. Results 3.1. Descriptive Statistics The study included a total of 759 pairs of children and parents. The average age of the parents was 63.09 ± 12.57 years, while the average age of the children was 37.29 ± 12.60 years. In terms of gender, there were more females than males in both the parent and child groups. Regarding educational level, the average education level of the parents was 2.28 ± 1.11, indicating that the majority of parents had completed middle school or lower. The children, on the other hand, had an average education level above middle school, with most having at least some high school education. In terms of health status, the average health utility score for parents was 0.90 ± 0.18, which was lower than that of the children, whose average health utility score was 0.97 ± 0.09. However, overall, the health status of the study participants was at a good level. The descriptive statistics of our samples are summarized in Table 1 . Table 1 Basic characteristics of variables. Variable Type Variable Name Coding Mean (Standard Deviation) Dependent Variable Father’s Health Life Quality Health Utility Value 0.90 (0.18) Independent Variable Educational Capital Illiterate = 1, Primary School = 2, Junior High = 3, High School = 4, College = 5, Bachelor and Above = 6 3.87 (1.39) Health Capital Health Utility Value 0.97 (0.09) Mediator Variable Social Support PSSS-F3 Perceived Social Support Scale, using Likert 7-point scoring method 16.62 (3.29) Moderating Variable Digital Health Literacy Whether internet or digital media has been used for health information (No = 0, Yes = 1) 0.33 (0.47) Control Variables Father’s Gender Male = 1, Female = 2 1.56 (0.50) Father’s Age Continuous variable 63.09 (12.57) Father’s Medical Insurance Participation Urban Worker’s Medical Insurance (No = 0, Yes = 1) 0.15 (0.36) Father’s Employment Status In employment = 0, Retired = 1, Unemployed = 2 1.59 (0.49) Father’s Education Level Illiterate = 1, Primary School = 2, Junior High = 3, High School = 4, College = 5, Bachelor and Above = 6 2.28 (1.11) Child’s Age Continuous variable 37.29 (12.60) Child’s Gender Male = 1, Female = 2 1.42 (0.39) Child’s Marital Status Unmarried = 1, Married = 2 0.82 (0.38) Number of Children Continuous variable 1.90 (1.11) Family Power Structure Traditional Power Type = 1, Tool Authority Type = 2, Emotional Authority Type = 3, Shared Authority Type = 4 2.20 (1.37) Family Type Core Family = 1, Main Family = 2, Joint Family = 3, Single-Parent Family = 4, Reconstructed = 5, DINK Family = 6, Empty-Nest Family = 7, Grandparent Family = 8 2.52 (2.05) Smoking No = 0, Yes = 1 0.23 (0.42) Drinking No = 0, Yes = 1 0.23 (0.42) Physical Exercise Average weekly exercise frequency in the last month 2.97 (3.37) Notes: Robust standard errors in parentheses. 3.2. Basic Regression Analysis We employed multiple linear regression to examine the relationship between parental health-related quality of life (HRQoL) and offspring human capital, with offspring's average education level and average health status as independent variables. Each model progressively introduced control variables to ensure the robustness of the findings. Model 1 presents the regression results with core independent variables, Model 2 represents a fixed effects model, Model 3 further includes individual demographic characteristics and health behavior variables, and Model 4 incorporates family characteristic variables, presenting the results step by step. In Model 1, the regression results indicate that offspring education human capital has a nonlinear relationship with parental health utility value (p < 0.01), forming an inverted U-shape. The data shows that when offspring's education level reaches college or higher, the improvement in parental HRQoL becomes slower as offspring's education level increases. Offspring health human capital is positively correlated with parental health utility value (p < 0.001). Model 2 is a fixed effects model, controlling for village-level differences. The regression results reveal that the differences in offspring education human capital, health human capital, and parental health utility value remain statistically significant. Specifically, offspring education human capital still shows a nonlinear relationship with parental health utility value (p < 0.01), while offspring health human capital is positively correlated with parental health utility value (p < 0.001). In Model 3, the regression results show that offspring education human capital, health human capital, and parental health utility value continue to exhibit statistical significance. Additionally, parental age (p < 0.01), employment status (p < 0.05), and physical exercise behavior (p < 0.05) all show statistically significant differences in parental health utility value. The variables such as parental education level, health insurance, smoking, and drinking do not have statistical significance on the health utility value of parents. In Model 4, after incorporating individual basic characteristics and family characteristics as control variables, shows that offspring education human capital, health human capital, and parental health utility value still exhibit statistical significance. Regarding individual characteristics, parental age (p < 0.01), employment status (p < 0.05), and physical exercise behavior (p < 0.05) all show statistically significant differences in parental health utility value. In terms of family characteristics, offspring marital status (p < 0.05) and family power structure (p < 0.05) are statistically significant factors affecting parental health utility value. The variables such as parental education level, health insurance, smoking, drinking, children's age, children's gender, number of children, and family type do not have statistical significance on the health utility value of parents. The detailed results are presented in Table 2 . Table 2 Regression results. Variable (1) (2) (3) (4) Education level kids 0.1028*** 0.0820** 0.0826*** 0.0789** (0.0254) (0.0252) (0.0247) (0.0252) I(education_level_kids^2) -0.0096** -0.0074* -0.0088** -0.0085** (0.0031) (0.0031) (0.0030) (0.0031) Health kids 0.3560*** 0.3657*** 0.3049*** 0.2833*** (0.0783) (0.0770) (0.0755) (0.0767) Age -0.0019** -0.0015* (0.0007) (0.0007) Gender 0.0265 + 0.0276 + (0.0153) (0.0154) Education level 0.0094 0.0048 (0.0072) (0.0073) Employment status -0.0330* -0.0361* (0.0155) (0.0155) Urban employee insurance -0.0203 -0.0162 (0.0255) (0.0255) Urban rural resident insurance -0.0374 -0.0334 (0.0264) (0.0265) Commercial insurance -0.0599 + -0.0733* (0.0344) (0.0347) Smoking 0.0296 0.0272 (0.0190) (0.0190) Drinking 0.0231 0.0202 (0.0182) (0.0183) Exercise frequency 0.0045* 0.0047* (0.0018) (0.0018) Age kids 0.0002 (0.0006) Gender kids -0.0033 (0.0158) Marital status 0.0446* (0.0181) Children num 0.0031 (0.0068) Family type -0.0044 (0.0032) Family power structure 0.0097* (0.0047) SD (Observations) 0.1693 0.1643 0.1638 Obs 759 759 759 759 R 2 0.1040 Notes: + p < 0.1, *p < 0.05,**p < 0.01, ***p < 0.001;Robust standard errors in parentheses. 3.3. Mediator Effect Analysis The results of Model 1 in the mediation analysis indicate that the educational capital of the offspring (p < 0.01) and their health capital (p < 0.01) have a positive effect on the health utility value of the parents. After including the mediating variable, perceived social support, the regression results of Model 2 show that perceived social support (p < 0.001) still has a statistically significant effect on the health utility value of the parents, and the two variables are significantly positively correlated. Detailed results can be found in Table 3 . Table 3 Mediation Effect Analysis of Perceived Social Support. Variable (1) (2) Education level kids 0.2707** 0.0652** (0.1048) (0.0252) Health kids 3.8113** 0.2653*** (1.4399) (0.0761) I(education level kids^2) -0.0070* (0.0030) PSSS 0.0085*** (0.0019) Control SD (Observations) 3.1007 0.1621 Obs 759 759 R 2 0.1330 0.2350 Notes: + p < 0.1, *p < 0.05,**p < 0.01, ***p < 0.001;Robust standard errors in parentheses. Under the condition of 1,000 Bootstrap iterations, the indirect effects of offspring's educational human capital and health capital were calculated, along with their corresponding 95% confidence intervals. The analysis reveals that the indirect effect of perceived social support remains significant (p < 0.01). Furthermore, the mediating effect of perceived social support accounts for a relatively larger proportion in the relationship between offspring's education and the enhancement of parental health-related quality of life. Detailed results are presented in Tables 4 and 5 . Table 4 Proportion of Mediation Effect in the Offspring Education-Perceived Social Support-Parental Health-Related Quality of Life Pathway. Estimate 95% CI Lower 95% CI Upper P ACME 0.03268 0.00609 0.07 <0.01 ADE 0.26463 0.11490 0.41 <0.01 Total Effect 0.29730 0.14937 0.45 <0.001 Prop Mediated 0.10890 0.02165 0.27 <0.01 Table 5 Proportion of Mediation Effect in the Offspring Health-Perceived Social Support-Parental Health-Related Quality of Life Pathway. Estimate 95% CI Lower 95% CI Upper P ACME 0.00231 0.00057 0.00 <0.01 ADE 0.06553 0.01588 0.11 <0.01 Total Effect 0.29730 0.01835 0.15 <0.01 Prop Mediated 0.06783 0.00801 0.15 <0.01 3.4. Moderating Effect Analysis As shown in Table 6 , the results of Model 1, which include the offspring's educational capital, digital health literacy, and the interaction term between offspring's educational capital and digital health literacy, indicate that after controlling for other variables, no direct moderating effect of digital health literacy was found in the relationship between offspring’s educational capital and the parents' health utility value. However, the results of Model 2 and Model 3 demonstrate that the interaction term between offspring’s educational capital and digital health literacy (p < 0.05) has a significant positive effect on perceived social support. This suggests that digital health literacy plays a moderating role in the impact of offspring’s education level on perceived social support, meaning that digital health literacy moderates the first half of the mediation path. Table 6 Moderating Effects of Digital Health Literacy in the “Offspring Education-Perceived Social Support-Health-Related Quality of Life” Mediation Pathway. Variable (1) (2) (3) Education level kids 0.0126 + 0.1603 0.0116* (0.0060) (0.1210) (0.005) Dhl -0.0197 -1.3847 + -0.0464 (0.0390) (0.7360) (0.0640) Education level kids×dhl 0.0052 0.4010* (0.0094) (0.1750) PSSS 0.0085** (0.0026) PSSS×Dhl 0.0027 (0.0038) SD (Observations) 0.1636 3.1060 0.1641 Obs 759 759 759 R 2 0.1960 0.1310 0.2180 Notes: + p < 0.1, *p < 0.05,**p < 0.01,***p < 0.001. Regarding offspring's health capital, Model 1 presents the estimated results after incorporating offspring's health capital, digital health literacy, and the interaction term between offspring's health capital and digital health literacy. After controlling for other variables, the interaction term between offspring's health capital and digital health literacy shows a significant negative effect on the parents' health utility value (p < 0.001). This suggests that digital health literacy negatively moderates the impact of offspring's health capital on parents' health life quality. Models 2 and 3 reveal that the interaction term between offspring's health capital and digital health literacy has a positive effect on perceived social support (p < 0.1). This indicates that in terms of the mediation effect, digital health literacy moderates the first half of the mediation path. Detailed results are presented in Table 7 : Table 7 Moderating Effects of Digital Health Literacy in the “Offspring Health-Perceived Social Support-Health-Related Quality of Life” Mediation Pathway. Variable (1) (2) (3) Health kids 0.6677*** 1.7086 0.3094*** (0.1166) (2.2140) (0.0760) Dhl 0.5118*** -4.3342 -0.0198 (0.1419) (2.6942) (0.0644) Health kids×Dhl -0.5166*** 4.8636 + (0.1461) (2.7735) PSSS 0.0085*** (0.0026) PSSS×Dhl 0.0017 (0.0038) SD (Observations) 0.1636 3.1060 0.1627 Obs 759 759 759 R 2 0.2230 0.1310 0.2320 Notes: + p < 0.1, *p < 0.05,**p < 0.01,***p < 0.001. 4. Discussion This study conducted a large-scale cross-sectional survey through household visits, exploring the relationship between children’s educational human capital, children’s health human capital, perceived social support, digital health literacy, and parents' health-related quality of life (HRQoL). Regarding children’s educational human capital, this study reveals an inverted U-shaped relationship between children’s education level and parents' HRQoL. Specifically, as children’s education level increases, parents' health-related quality of life significantly improves. However, once the education level reaches a certain threshold, the marginal effect on parents’ HRQoL gradually diminishes. In particular, when children’s education level is low, increasing education significantly improves parents’ health, as higher education is typically associated with stronger economic support, more comprehensive health knowledge, and broader social support resources. However, when children’s education level reaches college or higher, the marginal effect on parents’ health-related quality of life decreases. This may be because, as education levels increase, children may migrate to urban areas, and the reduced face-to-face support from children negatively impacts parents’ mental health, subsequently affecting their overall health. The finding of this inverted U-shaped relationship is consistent with some conclusions in existing literature. One study pointed out that, as parents enter old age, the absence of emotional support and daily care from children significantly weakens the psychological health benefits that higher education brings to rural parents, thereby affecting their health levels [ 48 ] . Other studys highlighted that children’s increased education level can improve parents' health through economic support and health knowledge transmission. However, as children's education level rises, especially when they migrate to urban areas, the separation between children and parents may lead to negative effects on parents' health with the diminishing marginal effect observed in our study [ 49 , 50 ] . Jia also pointed out that there is an inverted U-shaped relationship between years of education and family health, meaning that rural residents gain limited health benefits from higher education, and the health returns for highly educated individuals gradually diminish [ 14 ] . However, unlike previous studies that proposed a linear relationship where an increase in children’s education level significantly improves parents’ health-related quality of life [ 51 – 53 ] ,our study revealed pattern in the influence of education on parents’ health. In rural areas, the improvement in children’s education level not only affects parents' health through better health behaviors, increased economic support, and social capital accumulation, but is also influenced by factors such as the spatial separation between children and parents and the reduction of intergenerational support. As children’s education level becomes higher, the positive effects gradually weaken, likely due to changes in work and living arrangements resulting from urban-rural differences, increased life pressures, and reduced intergenerational interaction. Hence, hypothesis H 1a is supported. For the human capital of the next generation, research indicates a significant positive relationship between the health levels of the offspring and the health-related quality of life of the parents. This aligns with previous studies [ 54 ] , which suggest that when the next generation possesses high levels of health capital, it translates to better employment opportunities and higher income levels, enabling them to provide economic support to their parents and alleviate their financial burdens, thus improving the parents' quality of life. Alternatively, when the offspring have higher health capital, it reflects their better health status, reducing the care and support required from the parents, thereby easing the parents' psychological burden and stress. Therefore, hypothesis H 1b is supported. The findings of this study underscore the critical role of the offspring's health in the overall family well-being, highlighting the importance of enhancing health education and capacity building for the younger generation in family health management and policy-making. Furthermore, in the mediation effect test, the perception of social support strengthens the positive impact of the offspring's education on the parents' health-related quality of life. This is consistent with previous research, which indicates that elderly individuals who receive economic and emotional support from their children are more likely to adopt positive health behaviors, leading to improved physical and mental health [ 54 , 55 ] . For the relationship between offspring health and parental health-related quality of life, perceived social support acts as a full mediator. Specifically, the health of the offspring can improve the parents' quality of life by enhancing their social support, which is in line with prior studies. As a core component of elderly individuals' social relationships, intergenerational support from the next generation can significantly strengthen emotional closeness with elderly parents, boost positive emotions, maintain physical and mental health, and ultimately improve life quality [ 56 ] . Hence, hypothesis H 2 is confirmed. In the moderation effect test of digital health literacy, it was found that digital health literacy did not moderate the relationship between offspring education and the health-related quality of life of parents. This may be due to several factors. On one hand, the human capital of offspring education may influence the parents' health-related quality of life through indirect pathways, such as enhancing social support, which has already been empirically validated in the mediation effect test described earlier in this study. These pathways may not necessarily depend directly on digital health literacy. On the other hand, the majority of the parents surveyed in this study are elderly individuals aged 60 and above, residing in rural areas, with relatively low educational levels. Many of these parents lack the motivation to actively engage in learning or the corresponding ability to apply digital health technologies. As a result, digital health literacy did not have the expected moderating effect between offspring education and the health-related quality of life of the parents [ 51 ] . Regarding the relationship between offspring health human capital and the health-related quality of life of parents, digital health literacy played a significant negative moderating role, which is also consistent with previous research. Specifically, when parents have higher digital health literacy, they are more likely to actively use digital networks to obtain health information to manage and improve their health status, thereby reducing reliance on their children. In this case, the additional contribution of the offspring's health capital to the parents' health-related quality of life is relatively small [ 57 , 58 ] . Alternatively, distorted information and misinformation may lead to biased health perceptions and incorrect health behaviors among parents [ 59 , 60 ] . Furthermore, parents with a certain level of health information literacy tend to choose to believe health viewpoints that favor their own well-being, which may lead to conflicts in health management opinions or strategies between the offspring and parents, thereby impacting the parents' health-related quality of life [ 61 ] . Therefore, hypothesis H 3 is supported. The lack of significant impact from variables such as parental education level, health insurance, smoking, drinking, children's age, children's gender, number of children, and family type on the health utility value of parents may be attributed to several factors. First, the differences in sample characteristics could play a role. The study primarily involves a rural population, and the parents in the sample generally have lower education levels. This may limit the impact of variables like education and health insurance. In this context, the health utility value of parents may be more influenced by socio-economic and emotional support rather than by education level or health insurance alone. Second, there may be interactions between health behaviors and the social environment. For instance, the impact of behaviors like smoking and drinking could be influenced by multiple factors, such as family interactions. Especially in rural areas, the health status of parents is often more impacted by community and family support, which may diminish the independent effect of these variables. Additionally, factors such as children's gender, age, and family type may, in some cases, have potential effects on the health utility value of parents. However, these effects may be moderated by other variables (e.g, family economic status), which results in their lack of significance in the statistical model. In summary, based on the above research findings, the study proposes the following recommendations: Firstly, it is important to strengthen educational support for the next generation in rural areas and optimize intergenerational support mechanisms. While promoting rural education development, the government should also focus on the intergenerational support system between parents and children to prevent a decline in parents' health and well-being due to the migration of children. For example, rural community support networks can be established to foster emotional connections between children and parents, ensuring that parents continue to receive necessary health support even after their children migrate. Secondly, improving the health level of the next generation is crucial for promoting family health management. The health of children has a significant positive impact on the health-related quality of life of parents. The government should pay more attention to the health of children, particularly in rural areas, and promote health education and health promotion programs to enhance the health status of the next generation, thereby indirectly improving the health of parents. Simultaneously, it is essential to actively build a multi-level social support network. Perceived social support plays a significant mediating role between the human capital of children and the health-related quality of life of parents. The government should strengthen the development of social support networks in rural communities, encourage intergenerational interaction, and improve parents' perception of social support. For example, community activities and volunteer services can be organized to enhance the social support networks for rural parents, ultimately improving their health-related quality of life. Lastly, there is a need to enhance digital health literacy among rural parents. The negative moderating role of digital health literacy between children's health capital and parents' health highlights the need for the government to provide training on digital health literacy for rural parents, improving their ability to access health information through digital technologies. For example, community health lectures and digital skills training can be organized to help rural parents better utilize the internet for health information, reducing their reliance on their children. 5. Conclusions This study yields three main conclusions: (1) There is an inverted U-shaped relationship between offspring's educational human capital and parental health-related quality of life, while a linear positive correlation exists between offspring's health-related human capital and parental health-related quality of life. Moreover, in terms of marginal effects, offspring's health-related human capital has a greater impact on parental health-related quality of life compared to educational human capital. (2) Regarding the mediating effect of perceived social support, it plays a mediating role in the relationship between offspring's human capital endowment and parental health-related quality of life. (3) Concerning the moderating effect of digital health literacy, it does not significantly moderate the relationship between offspring's educational human capital and parental health-related quality of life. However, it plays an important moderating role in the mediating pathway of educational level influencing perceived social support. Additionally, digital health literacy negatively moderates the relationship between offspring's health-related human capital and parental health-related quality of life and also exerts a certain moderating effect in the pathway where offspring's health status influences perceived social support. Based on this, the study provides three meaningful conclusions by thoroughly examining the impact of children's human capital on the health-related quality of life of elderly parents in rural areas. However, it is important to note that this study employs cross-sectional data, which, while revealing correlations between variables, cannot definitively establish causal relationships. Therefore, we are unable to conclusively determine whether improvements in children's human capital directly lead to improvements in the health of elderly parents or whether other unmeasured potential variables are at play. Additionally, the study lacks experimental controls, which may result in the influence of external confounding variables on the findings. Future research could adopt a longitudinal design to establish clearer causal links, thereby enhancing internal validity. Moreover, the data in this study is sourced from rural areas in three different provinces, which provides some representativeness; however, the results are only applicable within a specific geographic context and may not fully represent rural areas nationwide. Factors such as regional disparities, economic development levels, and cultural backgrounds could affect the relationship between children's human capital and elderly parents' health-related quality of life. Future studies should expand the sample scope to include more diverse regions and socio-economic backgrounds, conducting cross-regional and cross-cultural comparative research. 6. Limitations First, when measuring digital health literacy, due to the limitations of the survey, this study used a single-item indicator to assess the digital health literacy of elderly parents. This may not fully capture the complexity of digital health literacy. While this indicator reflects elderly parents' ability to access health information in some aspects, future research could utilize digital health literacy scales to obtain more accurate results. Second, there are potential omitted variables. This study focuses on analyzing children's educational and health-related human capital but overlooks other important factors that may influence elderly parents' health, such as family economic status and community healthcare resources. These omitted variables could affect the accuracy and comprehensiveness of the findings. Future studies should consider these factors to refine the theoretical framework. In conclusion, this study provides valuable insights into the impact of children's human capital on elderly parents' health-related quality of life, contributing to the exploration of healthy aging and intergenerational health transmission. However, the limitations in the research design remind us to exercise caution when interpreting the results. Future studies need to address these limitations by employing more rigorous experimental designs, controlling for a broader range of variables, and conducting cross-regional and cross-cultural comparisons to further validate and expand the conclusions of this study. Abbreviations HRQoL Health-Related Quality of Life Declarations Ethics and consent to participate The study was conducted in accordance with the Helsinki Declaration. The study was conducted in accordance with the Declaration of Helsinki and approved by the National Natural Science Foundation of China (Project Approval No.72074084). Participants voluntarily participated, were informed about the survey’s purpose, answer methods, and precautions, and signed informed consent forms. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare no conflicts of interest. Funding This research received by the National Natural Science Foundation of China (Project Approval No. 72074084). Authors' contributions Conceptualization, X.Z, C.J ,P.R,; methodology, C.J; data curation, C.J; writing—original draft preparation, P.R, C.J; writing—review and editing, P.R, J.J, J.X, M.C; supervision, X.Z; project administration, X.Z. All authors have read and agreed to the published version of the manuscript. Acknowledgements We thank all the participants who participated in the study. An explanation of why your manuscript should be published in BMC Public Health Focusing on intergenerational health support mechanisms in the context of aging in rural China, this study combines family systems theory and digital inclusion perspectives to explore the impact of offspring human capital (education and health) on the health-related quality of life of rural fathers. The choice to submit the manuscript to BMC Public Health was based on the following reasons. First, the study focuses on the health-related quality of life (HRQoL) of rural middle-aged and elderly fathers, and explores the intergenerational transmission of offspring human capital, which is a direct response to BMC Public Health's focus on the issues of “health interventions in aging societies” and “health inequalities in families”. This directly responds to BMC Public Health's focus on “health interventions in an aging society” and “family health inequalities”. Second, the study innovatively introduces “digital health literacy” as a moderator variable, revealing the complexity of intergenerational health resource transmission in the context of digitization, which is highly consistent with BMC Public Health's focus on the theme of “digital technology for health equity”. This is highly consistent with BMC Public Health's focus on the theme of “digital technology for health equity”. In addition, based on Chinese rural data, the study analyzes the health challenges faced by the elderly in low- and middle-income countries with significant urban-rural disparities and accelerated aging, and provides universal conclusions for developing countries, which is in line with BMC Public Health's mission of promoting “global health equity”. In conclusion, this study not only fills the research gap in the field of intergenerational health transmission, but also provides a scientific basis for the global healthy aging strategy through a digital perspective. An explanation of any issues relating to journal policies This study complies with the journal policy of BMC Public Health . A declaration of any potential competing interests The authors declare that there are no potential conflicts of interest in this study. Confirmation that all authors have approved the manuscript for submission All authors have fully reviewed and approved this manuscript for submission to BMC Public Health , ensuring that all content in the manuscript is accurate and agreeing to make changes and improvements as required by the journal. Confirmation that the content of the manuscript has not been published, or submitted for publication elsewhere This manuscript is an original study and has not been published in or submitted to other journals or platforms. All data and analysis results were independently performed by our research team and did not involve any form of duplicate submissions or plagiarism. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6299719","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456624540,"identity":"f875460b-f1a0-40b1-8207-0dad27635fae","order_by":0,"name":"Changli Jia","email":"","orcid":"","institution":"1 Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":false,"prefix":"","firstName":"Changli","middleName":"","lastName":"Jia","suffix":""},{"id":456624541,"identity":"a14ec665-5d6b-42ad-a496-60058de4e22b","order_by":1,"name":"Panpan Ren","email":"","orcid":"","institution":"1 Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":false,"prefix":"","firstName":"Panpan","middleName":"","lastName":"Ren","suffix":""},{"id":456624542,"identity":"00242b0f-f3be-4408-9ac8-d91863b55fd5","order_by":2,"name":"Jingjing Jia","email":"","orcid":"","institution":"1 Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":false,"prefix":"","firstName":"Jingjing","middleName":"","lastName":"Jia","suffix":""},{"id":456624543,"identity":"6060d880-7a1e-4b68-afee-375937f2df6c","order_by":3,"name":"Jinglin Xu","email":"","orcid":"","institution":"1 Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":false,"prefix":"","firstName":"Jinglin","middleName":"","lastName":"Xu","suffix":""},{"id":456624544,"identity":"7dabcb0e-e458-42fb-8365-367956b49323","order_by":4,"name":"Mengyao Chen","email":"","orcid":"","institution":"1 Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":false,"prefix":"","firstName":"Mengyao","middleName":"","lastName":"Chen","suffix":""},{"id":456624545,"identity":"79cfe985-a547-4936-857b-3fa6c013adfd","order_by":5,"name":"Xiang Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6klEQVRIiWNgGAWjYDACCTB5gIENRH0wsLEjTQvjjIK0ZOK1gAAzz4dDjA2EdMjPbn728EvNncQ+9rOHX9sYHGBmYD98dAM+LYxzjpkbyxx7ZszGk5dmnWNwh4+BJy3tBj4tzBIJZtKSDYfl2BhyzIxzDJ4xM0jwmOHVwiaR/g2khYeN/42ZsYXBYcYGQlp4JHLMJD+CbJHIMX7MQIwWCYmcMmmGY4eN2STemDH2GKQlsxHyi/yM9G2SP2oOJ87vzzH+8OOPjR0/++FjeLWAADMPzF9gkpByEGD8AdX6gRjVo2AUjIJRMPIAAMmGRtGD10qXAAAAAElFTkSuQmCC","orcid":"","institution":"1 Huazhong University of Science and Technology Tongji Medical College","correspondingAuthor":true,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-03-25 03:53:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6299719/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6299719/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105741584,"identity":"934b2f28-6896-4b1e-b0cc-02eb814be3ef","added_by":"auto","created_at":"2026-03-30 13:13:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1393736,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6299719/v1/29607f16-0bdb-43bf-a4c8-6978ff6a430b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Research on the Impact Mechanism of Offspring Human Capital Endowment on the Health-Related Quality of Life of Rural Fathers from the Perspective of Digital Integration","fulltext":[{"header":"1. Background","content":"\u003cp\u003ePopulation aging has become a significant global issue in terms of both healthcare and social demographics. According to the World Health Organization, China is one of the countries with the fastest aging population growth. By 2040, it is expected that the proportion of people aged 60 and above in China will reach 28%\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. By the end of 2024, there will be 310.31\u0026nbsp;million elderly people aged 60 and above in China, exceeding 300\u0026nbsp;million for the first time; the population aged 65 and above will be 220.23\u0026nbsp;million, accounting for 15.6% of the total\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. In addition, due to the gap between urban and rural economic and social development and the impact of population migration, the age structure of China's population is characterized by significant urban-rural differences, and the trend of population aging in rural areas is bound to be more severe. According to life course theory, elderly individuals in the later stages of life are more likely to experience health problems, particularly with a significant increase in the prevalence of chronic diseases, which can place a heavy burden on social, economic, and healthcare systems. In this context, exploring intergenerational health support mechanisms is crucial for improving the quality of life for elderly individuals in rural areas. Research indicates that human capital plays an increasingly important role in improving individual health outcomes\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, with a significant positive correlation between higher education levels and longer life expectancy, while lower education levels negatively impact life expectancy\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. Family Systems Theory further emphasizes that the family is an interactive whole, where the emotions, behaviors, and health responses of family members influence each other\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. A large body of research has focused on the impact of parents on children's health, particularly how parental health behaviors significantly affect children's physical and mental health\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. However, intergenerational interaction involves not only the influence of parents on children's health but also the impact of offspring on parental health, which has long been neglected in academic literature. Despite the release of the \"14th Five-Year Plan for Healthy Aging\" by the National Health Commission of the People's Republic of China in 2022, emphasizing that \"the family is the first line of defense for health\" and further highlighting the key role of family involvement in maintaining the health of elderly individuals\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e, existing research still faces three major limitations: First, much of the focus remains on the role of education as a unidimensional human capital factor, overlooking the synergistic effects of health as a core dimension of human capital; second, there is an overemphasis on the unidirectional influence of parents on offspring, with a lack of systematic exploration of the pathways through which offspring human capital can benefit parental health; third, there is insufficient analysis of the multidimensional nature of family support mechanisms (economic, emotional, informational) and the moderating effects of technology in the digital age.\u003c/p\u003e \u003cp\u003eTo address the aforementioned gaps, this study constructs an analytical framework based on Family Systems Theory, focusing on the differentiated impact of offspring's \u0026ldquo;education-health\u0026rdquo; dual-dimensional human capital on the health and quality of life of rural parents. Previous research on human capital and health has shown that human capital investment has a positive impact on population health, with individuals possessing higher levels of human capital\u0026mdash;especially those with higher education\u0026mdash;typically demonstrating better cognitive abilities regarding their health behaviors \u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Research indicates that the level of human capital investment in offspring is a key factor influencing the health disparities of elderly parents\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e, with offspring's education level significantly affecting parental health behaviors, promoting smoking cessation, and improving overall health conditions\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. However, some studies have also found an inverted U-shaped relationship between years of education and family health, suggesting that rural residents derive limited health benefits from higher education, and the health returns for highly educated individuals tend to diminish over time\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Nonetheless, overall, offspring education still positively impacts the health quality of rural parents, although this effect weakens over time. Most studies have primarily examined human capital from the single dimension of education, while neglecting the health dimension\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Some scholars have recognized that both education and health are core factors influencing quality of life\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. With declining fertility rates and increasing aging, health as an important component of human capital has attracted growing attention from researchers. For example, some studies have explored the impact of health human capital on positive emotions, happiness, and the tendency toward elder abuse\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Individuals with strong health human capital typically exhibit higher levels of happiness and life satisfaction, thus maintaining a higher quality of life. This study aims to fill this gap by exploring how the human capital of the younger generation, through education and health, influences the health and quality of life of the older generation. Through the above analysis, it can be observed that offspring with higher education levels are better able to provide various health resources for their parents, including more health knowledge, health information, and health behaviors, all of which have a positive impact on parental health\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e. However, due to the constraints of the urban-rural dual household registration system, as the education level of rural offspring increases, the likelihood of separation between offspring and parents also increases. In such cases, parents often face significant life pressures, including daily labor and economic stress, which in turn affect their health improvement. Thus, we propose the following hypothesis H1a: There is an inverted U-shaped relationship between offspring education level and rural parental health quality of life. That is, as the education level of offspring increases, parental health quality of life first improves and then stabilizes. Additionally, from the perspective of intergenerational transmission, when offspring possess high levels of health human capital, they typically gain more economic resources, income, and opportunities, leading to higher socioeconomic status. In the unique context of China, this also leads to reciprocal support for parents, alleviating their retirement and living pressures, thereby improving parental health quality of life. Hence, we propose the following hypothesis H1b: There is a positive correlation between offspring health status and parental health quality of life. That is, offspring health status typically influences parental health by directly providing health knowledge and resources.\u003c/p\u003e \u003cp\u003eFurthermore, human capital not only directly affects health but can also improve individual health through various potential mechanisms\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Existing research indicates that human capital can enhance public health through economic support, social capital, and living arrangements\u003csup\u003e[\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e. With the development of positive psychology, the impact of perceived social support on individual health outcomes has become increasingly profound. The more social support individuals receive from family, friends, and significant others, the less likely they are to experience negative mental health issues such as depression and anxiety\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. The social support buffering model suggests that perceived social support provides psychological energy, helps regulate negative emotions, and facilitates access to social resources\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis buffering effect manifests in several forms: First, economic support, where offspring's support for their parents can be seen as an increase in individual income, providing financial assistance to improve parents' quality of life\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e; second, emotional support, where strong family relationships affect offspring's willingness to provide emotional care for their parents. The closer the parent-child relationship, the more likely offspring are to engage in reciprocal behaviors, promoting mutual concern for each other's health and encouraging healthy behaviors\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e; third, informational support, where offspring assist their parents in accessing online health information, fostering a \"bottom-up\" model of intergenerational interaction that influences parents' self-awareness and health consciousness\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e. The above literature suggests that offspring human capital is closely related to parental perceived social support. Offspring with higher human capital are able to provide more social support to their elderly parents, including economic, emotional, and informational support, thereby enhancing the social support that parents perceive and helping them cope with negative life events. In contrast, offspring with lower human capital often leads to less perceived social support for their parents, which in turn affects their health. Based on this, we propose the following hypothesis H2: Perceived social support mediates the relationship between offspring human capital (education and health) and parental health quality of life.\u003c/p\u003e \u003cp\u003eFurthermore, digital health literacy is the combination of digital literacy and health literacy, referring to an individual's ability to access information through digital devices and apply this information to solve health-related issues\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. With the development of the internet and information and communication technologies, digitalization has become a mainstream trend in societal development, with digital media gradually becoming the preferred source for individuals seeking health information\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. From the perspective of health management, the ability to access online health information plays a crucial role in helping individuals independently understand disease symptoms, the pros and cons of medical treatments, and improving public health management and decision-making capabilities\u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/sup\u003e. Previous studies have highlighted the importance of improving digital health literacy in promoting positive aging\u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e, noting that internet use can protect the cognitive function of elderly individuals and improve their health\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIt can thus be concluded that accessing and utilizing digital health information is a key tool for improving healthy aging. It is a critical factor enabling middle-aged and elderly individuals to benefit from the digitalization of healthcare services, directly influencing their future health quality of life. Therefore, considering that the digital health literacy of parents may affect their ability to utilize health information provided by their offspring, this study explores how digital health literacy moderates the impact of offspring human capital on parental health quality of life. Traditionally, health information transmission has been viewed as flowing from parents to children, with health knowledge and information being passed down. However, for older rural individuals who have limited internet skills and health information-seeking abilities, younger offspring with more abundant human capital resources and stronger digital technology skills may be better positioned to provide health information. Parents with strong digital health literacy are more likely to benefit from these resources, thereby improving their quality of life. Thus, we propose the following hypothesis H3: Digital health literacy moderates the relationship between offspring human capital and parental health quality of life.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.1 Study design, setting, and participants\u003c/em\u003e\u003c/h2\u003e \u003cp\u003eThe data used in this study were collected through field research conducted by our research team in the provinces of Zhejiang, Chongqing, and Gansu from July to August 2023. The survey employed a stratified random sampling method. In each province (or city), two counties (or districts) were randomly selected based on their economic development levels. For each selected county (or district), two towns were randomly chosen, and for each town, two administrative villages were randomly selected, resulting in a total of 24 villages. The survey was conducted using a household approach to cluster sampling within the selected villages. A total of 2,000 questionnaires were distributed, and 1,860 were returned, resulting in a response rate of 93%. The survey included 3,308 participants, indicating good data collection effectiveness.\u003c/p\u003e \u003cp\u003eSince this study aims to investigate the health relationships between the younger and older generations, we excluded empty-nest families and dual-income-no-kids (DINK) families during the sample selection process. Consequently, a total of 345 families were included in the statistical analysis. The inclusion criteria were as follows: the basic unit of the survey was the family, which included the older generation and their cohabiting children; the age of the younger generation was \u0026ge;\u0026thinsp;18 years; and they had been residing at home for at least six months during the survey. After excluding missing values for various variables, a final matched sample of 759 pairs of younger and older generations was included in the statistical analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e\u003cem\u003e2.2. Study variables\u003c/em\u003e\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. The Dependent Variable\u003c/h2\u003e \u003cp\u003eHealth-related quality of life will be measured using the European Five Dimensions Health Scale (EQ-5D-3L). It evaluates health-related quality of life across five dimensions: mobility (MO), self-care (SC), usual activities (UA), pain/discomfort (PD), and anxiety/depression (AD). Respondents assess their health status in each dimension by selecting one of three levels: no problems, mild problems, or severe problems. These responses are then converted into a health utility value (U) using a utility scoring system.\u003c/p\u003e \u003cp\u003eIn this study, The health utility values (U) for the target population will be calculated using the conversion table developed by Liu et al\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. The calculation of the health utility values is performed using the formula:\u003c/p\u003e \u003cp\u003eU\u0026thinsp;=\u0026thinsp;1-(MO\u003csub\u003en\u003c/sub\u003e+SC\u003csub\u003en\u003c/sub\u003e+UA\u003csub\u003en\u003c/sub\u003e+PD\u003csub\u003en\u003c/sub\u003e+AD\u003csub\u003en\u003c/sub\u003e), n\u0026thinsp;=\u0026thinsp;1,2,3,4,5\u003c/p\u003e \u003cp\u003eThe health utility value ranges from \u0026minus;\u0026thinsp;0.391 to 1.000, with higher scores indicating better health status.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. The Independent Variable\u003c/h2\u003e \u003cp\u003eIn this study, the concept of human capital for offspring is represented by two proxy variables: health human capital and educational human capital. Specifically, health human capital is measured using the average health utility value of the offspring, while educational human capital is assessed based on the average years of education of the offspring.\u003c/p\u003e \u003cp\u003eThe health utility value of offspring is derived from the EQ-5D-3L scores of all surveyed offspring. In contrast, the average health utility value of offspring refers to the mean health utility value across all offspring in the study sample, serving as an indicator of the overall health status of the offspring population.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Mediating Variable\u003c/h2\u003e \u003cp\u003eSocial support will be measured using the Perceived Social Support Scale (PSSS-SF3), developed by MH Zimet et al. in 1987, and translated for use by Chinese scholar Jiang Qianjin. This scale comprises three dimensions, including emotional support, informational support, and tangible support that individuals can receive from family, friends, or other social networks. All measurement items utilize a 7-point Likert scale, where higher scores indicate a stronger perception of social support from external sources by the parents.\u003c/p\u003e \u003cp\u003eIn this study, social support was measured based on responses from parents, rather than their offspring. The aim was to assess the subjective perception of support that rural elderly parents receive from their children, including emotional support, informational support, and tangible support. All questionnaire items were directly answered by the parents to ensure that the data accurately reflect their genuine perceptions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Moderating Variable\u003c/h2\u003e \u003cp\u003eDigital health literacy has often been measured using instruments such as the eHealth Literacy Scale (eHEALS)\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003eand the Digital Health Literacy Instrument (DHLI)\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Additionally, scholars in China have developed a community-based digital health literacy assessment scale tailored to the characteristics of older adults, which includes three dimensions: the ability to access and assess digital health information, interaction capabilities, and application skills\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. Due to limitations in the content of the questionnaire survey, referring to existing research\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e,this study primarily assesses the digital health information acquisition level of elderly parents in rural areas by asking them whether they have used digital media to access health-related information. This single-item measure serves as an indicator of their engagement with digital health resources.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5. Control Variable\u003c/h2\u003e \u003cp\u003eFamily structure is a crucial determinant of family social capital\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. Different structural forms of families exhibit variations in resource allocation and functional realization, which, in turn, affect the human capital of the offspring\u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. Research indicates that family structure profoundly influences individual physical health and psychological development\u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e. Additionally, family type plays a significant role in the health behaviors of offspring\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e.Therefore, drawing from prior studies, this research selects individual demographic characteristics, health behaviors, and family characteristics as control variables. Specifically, individual demographic characteristics include age, gender, educational attainment, and employment status; health behaviors encompass smoking, alcohol consumption, and physical exercise; while family characteristics consist of the offspring's age, gender, family power structure, and family type.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Data Analysis\u003c/h2\u003e \u003cp\u003eTo analyze the impact of offspring human capital on parental health-related quality of life, this study establishes the following regression model:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{pheal}_{i}={c}_{0}+{c}_{1}{edu}_{i}+{c}_{2}{heal}_{i}+\\sum\\:{c}_{3}{x}_{i}+{{\\epsilon\\:}_{1}}_{i}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this model,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\:pheal}_{i}\\)\u003c/span\u003e\u003c/span\u003erepresents the health utility value of the parent. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{edu}_{i}\\:\\)\u003c/span\u003e\u003c/span\u003edenotes the educational human capital of the offspring. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{heal}_{i}\\:\\)\u003c/span\u003e\u003c/span\u003eindicates the health human capital of the offspring. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{x}_{i}\\:\\)\u003c/span\u003e\u003c/span\u003eincludes the control variables.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{0}\\:\\)\u003c/span\u003e\u003c/span\u003eis the constant term. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{1}\\)\u003c/span\u003e\u003c/span\u003e、\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{2}\\)\u003c/span\u003e\u003c/span\u003e、\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{c}_{3}\\)\u003c/span\u003e\u003c/span\u003e are the coefficients to be estimated.\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\epsilon\\:}_{1}}_{i}\\:\\)\u003c/span\u003e\u003c/span\u003erepresents the random disturbance term.\u003c/p\u003e \u003cp\u003eIn this study, the data collected were double-checked using EpiData software to ensure data entry quality. During the statistical analysis phase, R version 4.2.3 was used for data analysis. Descriptive statistics were employed to describe the basic demographic characteristics. Multiple linear regression was used to analyze the influencing factors. The bootstrap method was applied to identify mediation effects, and moderation analysis was conducted to examine the moderating role of digital health literacy. A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Descriptive Statistics\u003c/h2\u003e \u003cp\u003eThe study included a total of 759 pairs of children and parents. The average age of the parents was 63.09\u0026thinsp;\u0026plusmn;\u0026thinsp;12.57 years, while the average age of the children was 37.29\u0026thinsp;\u0026plusmn;\u0026thinsp;12.60 years. In terms of gender, there were more females than males in both the parent and child groups. Regarding educational level, the average education level of the parents was 2.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11, indicating that the majority of parents had completed middle school or lower. The children, on the other hand, had an average education level above middle school, with most having at least some high school education. In terms of health status, the average health utility score for parents was 0.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18, which was lower than that of the children, whose average health utility score was 0.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09. However, overall, the health status of the study participants was at a good level. The descriptive statistics of our samples are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\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\u003eBasic characteristics of variables.\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\u003eVariable\u003c/p\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVariable Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCoding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003cp\u003e(Standard Deviation)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u0026rsquo;s Health Life Quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHealth Utility Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003cp\u003e(0.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndependent Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEducational Capital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIlliterate\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003ePrimary School\u0026thinsp;=\u0026thinsp;2,\u003c/p\u003e \u003cp\u003eJunior High\u0026thinsp;=\u0026thinsp;3,\u003c/p\u003e \u003cp\u003eHigh School\u0026thinsp;=\u0026thinsp;4,\u003c/p\u003e \u003cp\u003eCollege\u0026thinsp;=\u0026thinsp;5,\u003c/p\u003e \u003cp\u003eBachelor and Above =\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.87\u003c/p\u003e \u003cp\u003e(1.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth Capital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHealth Utility Value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003cp\u003e(0.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMediator\u003c/p\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSocial Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePSSS-F3 Perceived Social Support Scale, using Likert\u003c/p\u003e \u003cp\u003e7-point scoring method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003cp\u003e(3.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerating Variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDigital Health Literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhether internet or digital\u003c/p\u003e \u003cp\u003emedia has been used for\u003c/p\u003e \u003cp\u003ehealth information\u003c/p\u003e \u003cp\u003e(No\u0026thinsp;=\u0026thinsp;0, Yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003cp\u003e(0.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"13\" rowspan=\"14\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u0026rsquo;s Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003eFemale\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003cp\u003e(0.50)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u0026rsquo;s Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.09\u003c/p\u003e \u003cp\u003e(12.57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u0026rsquo;s Medical\u003c/p\u003e \u003cp\u003eInsurance Participation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUrban Worker\u0026rsquo;s Medical Insurance (No\u0026thinsp;=\u0026thinsp;0, Yes\u0026thinsp;=\u0026thinsp;1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003cp\u003e(0.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u0026rsquo;s Employment\u003c/p\u003e \u003cp\u003eStatus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIn employment\u0026thinsp;=\u0026thinsp;0,\u003c/p\u003e \u003cp\u003eRetired\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003eUnemployed\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.59\u003c/p\u003e \u003cp\u003e(0.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFather\u0026rsquo;s Education Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIlliterate\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003ePrimary School\u0026thinsp;=\u0026thinsp;2,\u003c/p\u003e \u003cp\u003eJunior High\u0026thinsp;=\u0026thinsp;3,\u003c/p\u003e \u003cp\u003eHigh School\u0026thinsp;=\u0026thinsp;4,\u003c/p\u003e \u003cp\u003eCollege\u0026thinsp;=\u0026thinsp;5,\u003c/p\u003e \u003cp\u003eBachelor and Above =\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003cp\u003e(1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChild\u0026rsquo;s Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.29\u003c/p\u003e \u003cp\u003e(12.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChild\u0026rsquo;s Gender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMale\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003eFemale\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42\u003c/p\u003e \u003cp\u003e(0.39)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChild\u0026rsquo;s Marital Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnmarried\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003eMarried\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003cp\u003e(0.38)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eContinuous variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003cp\u003e(1.11)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamily Power Structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTraditional Power Type\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003eTool Authority Type\u0026thinsp;=\u0026thinsp;2,\u003c/p\u003e \u003cp\u003eEmotional Authority Type\u0026thinsp;=\u0026thinsp;3, Shared Authority Type\u0026thinsp;=\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003cp\u003e(1.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamily Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCore Family\u0026thinsp;=\u0026thinsp;1,\u003c/p\u003e \u003cp\u003eMain Family\u0026thinsp;=\u0026thinsp;2,\u003c/p\u003e \u003cp\u003eJoint Family\u0026thinsp;=\u0026thinsp;3,\u003c/p\u003e \u003cp\u003eSingle-Parent Family\u0026thinsp;=\u0026thinsp;4,\u003c/p\u003e \u003cp\u003eReconstructed\u0026thinsp;=\u0026thinsp;5,\u003c/p\u003e \u003cp\u003eDINK Family\u0026thinsp;=\u0026thinsp;6,\u003c/p\u003e \u003cp\u003eEmpty-Nest Family\u0026thinsp;=\u0026thinsp;7,\u003c/p\u003e \u003cp\u003eGrandparent Family\u0026thinsp;=\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003cp\u003e(2.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u0026thinsp;=\u0026thinsp;0, Yes\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e(0.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDrinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u0026thinsp;=\u0026thinsp;0, Yes\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003cp\u003e(0.42)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical Exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAverage weekly exercise\u003c/p\u003e \u003cp\u003efrequency in the last month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003cp\u003e(3.37)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNotes: Robust standard errors in parentheses.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Basic Regression Analysis\u003c/h2\u003e \u003cp\u003eWe employed multiple linear regression to examine the relationship between parental health-related quality of life (HRQoL) and offspring human capital, with offspring's average education level and average health status as independent variables. Each model progressively introduced control variables to ensure the robustness of the findings. Model 1 presents the regression results with core independent variables, Model 2 represents a fixed effects model, Model 3 further includes individual demographic characteristics and health behavior variables, and Model 4 incorporates family characteristic variables, presenting the results step by step.\u003c/p\u003e \u003cp\u003eIn Model 1, the regression results indicate that offspring education human capital has a nonlinear relationship with parental health utility value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), forming an inverted U-shape. The data shows that when offspring's education level reaches college or higher, the improvement in parental HRQoL becomes slower as offspring's education level increases. Offspring health human capital is positively correlated with parental health utility value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eModel 2 is a fixed effects model, controlling for village-level differences. The regression results reveal that the differences in offspring education human capital, health human capital, and parental health utility value remain statistically significant. Specifically, offspring education human capital still shows a nonlinear relationship with parental health utility value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while offspring health human capital is positively correlated with parental health utility value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eIn Model 3, the regression results show that offspring education human capital, health human capital, and parental health utility value continue to exhibit statistical significance. Additionally, parental age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), employment status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and physical exercise behavior (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) all show statistically significant differences in parental health utility value. The variables such as parental education level, health insurance, smoking, and drinking do not have statistical significance on the health utility value of parents.\u003c/p\u003e \u003cp\u003eIn Model 4, after incorporating individual basic characteristics and family characteristics as control variables, shows that offspring education human capital, health human capital, and parental health utility value still exhibit statistical significance. Regarding individual characteristics, parental age (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), employment status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and physical exercise behavior (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) all show statistically significant differences in parental health utility value. In terms of family characteristics, offspring marital status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and family power structure (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) are statistically significant factors affecting parental health utility value. The variables such as parental education level, health insurance, smoking, drinking, children's age, children's gender, number of children, and family type do not have statistical significance on the health utility value of parents. The detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\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\u003eRegression 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\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level kids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1028***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0820**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0826***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0789**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.0254)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0252)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0247)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0252)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI(education_level_kids^2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0096**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0074*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0088**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0085**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.0031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth kids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3560***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3657***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3049***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2833***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.0783)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0770)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0755)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0767)\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-0.0019**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0015*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0007)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\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\u003e0.0265\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0276\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0154)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\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\u003e0.0094\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0073)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployment status\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-0.0330*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0361*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0155)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban employee insurance\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-0.0203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0162\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0255)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban rural resident insurance\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-0.0374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0264)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0265)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommercial insurance\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-0.0599\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0733*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0344)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0347)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\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\u003e0.0296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0190)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0190)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrinking\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\u003e0.0231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0182)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0183)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExercise frequency\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\u003e0.0045*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0047*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0018)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge kids\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0006)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender kids\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0033\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0158)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0446*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0181)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChildren num\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0068)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily type\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.0044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0032)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily power structure\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0097*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.0047)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD (Observations)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1638\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eNotes:\u003csup\u003e+\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.1, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05,**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001;Robust standard errors in parentheses.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Mediator Effect Analysis\u003c/h2\u003e \u003cp\u003eThe results of Model 1 in the mediation analysis indicate that the educational capital of the offspring (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and their health capital (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) have a positive effect on the health utility value of the parents. After including the mediating variable, perceived social support, the regression results of Model 2 show that perceived social support (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) still has a statistically significant effect on the health utility value of the parents, and the two variables are significantly positively correlated. Detailed results can be found in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\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 Effect Analysis of Perceived Social Support.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \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\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level kids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2707**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0652**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.1048)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0252)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth kids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.8113**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2653***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.4399)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0761)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI(education level kids^2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.0070*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0030)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSSS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0085***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.0019)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD (Observations)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.1007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.2350\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eNotes:\u003csup\u003e+\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.1, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05,**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001;Robust standard errors in parentheses.\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\u003eUnder the condition of 1,000 Bootstrap iterations, the indirect effects of offspring's educational human capital and health capital were calculated, along with their corresponding 95% confidence intervals. The analysis reveals that the indirect effect of perceived social support remains significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Furthermore, the mediating effect of perceived social support accounts for a relatively larger proportion in the relationship between offspring's education and the enhancement of parental health-related quality of life. Detailed results are presented in Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\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\u003eProportion of Mediation Effect in the Offspring Education-Perceived Social Support-Parental Health-Related Quality of Life Pathway.\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI Lower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI Upper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.26463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.11490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.14937\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProp Mediated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.10890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\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\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\u003eProportion of Mediation Effect in the Offspring Health-Perceived Social Support-Parental Health-Related Quality of Life Pathway.\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEstimate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI Lower\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI Upper\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.00231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Effect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.29730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProp Mediated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.06783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00801\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Moderating Effect Analysis\u003c/h2\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, the results of Model 1, which include the offspring's educational capital, digital health literacy, and the interaction term between offspring's educational capital and digital health literacy, indicate that after controlling for other variables, no direct moderating effect of digital health literacy was found in the relationship between offspring\u0026rsquo;s educational capital and the parents' health utility value.\u003c/p\u003e \u003cp\u003eHowever, the results of Model 2 and Model 3 demonstrate that the interaction term between offspring\u0026rsquo;s educational capital and digital health literacy (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) has a significant positive effect on perceived social support. This suggests that digital health literacy plays a moderating role in the impact of offspring\u0026rsquo;s education level on perceived social support, meaning that digital health literacy moderates the first half of the mediation path.\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\u003eModerating Effects of Digital Health Literacy in the \u0026ldquo;Offspring Education-Perceived Social Support-Health-Related Quality of Life\u0026rdquo; Mediation Pathway.\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level kids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0126\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0116*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.0060)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.1210)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDhl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.0197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.3847\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.0390)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.7360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0640)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level kids\u0026times;dhl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4010*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.0094)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.1750)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSSS\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\u003e0.0085**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0026)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSSS\u0026times;Dhl\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\u003e0.0027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0038)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD (Observations)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1641\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes:\u003csup\u003e+\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.1, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05,**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01,***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRegarding offspring's health capital, Model 1 presents the estimated results after incorporating offspring's health capital, digital health literacy, and the interaction term between offspring's health capital and digital health literacy. After controlling for other variables, the interaction term between offspring's health capital and digital health literacy shows a significant negative effect on the parents' health utility value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This suggests that digital health literacy negatively moderates the impact of offspring's health capital on parents' health life quality.\u003c/p\u003e \u003cp\u003eModels 2 and 3 reveal that the interaction term between offspring's health capital and digital health literacy has a positive effect on perceived social support (p\u0026thinsp;\u0026lt;\u0026thinsp;0.1). This indicates that in terms of the mediation effect, digital health literacy moderates the first half of the mediation path. Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\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\u003eModerating Effects of Digital Health Literacy in the \u0026ldquo;Offspring Health-Perceived Social Support-Health-Related Quality of Life\u0026rdquo; Mediation Pathway.\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth kids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6677***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3094***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.1166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.2140)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0760)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDhl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5118***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.3342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.0198\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.1419)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.6942)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.0644)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth kids\u0026times;Dhl\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.5166***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.8636\u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.1461)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2.7735)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSSS\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\u003e0.0085***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0026)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSSS\u0026times;Dhl\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\u003e0.0017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\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(0.0038)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD (Observations)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1636\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1627\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNotes:\u003csup\u003e+\u003c/sup\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.1, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05,**p\u0026thinsp;\u0026lt;\u0026thinsp;0.01,***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study conducted a large-scale cross-sectional survey through household visits, exploring the relationship between children\u0026rsquo;s educational human capital, children\u0026rsquo;s health human capital, perceived social support, digital health literacy, and parents' health-related quality of life (HRQoL).\u003c/p\u003e \u003cp\u003eRegarding children\u0026rsquo;s educational human capital, this study reveals an inverted U-shaped relationship between children\u0026rsquo;s education level and parents' HRQoL. Specifically, as children\u0026rsquo;s education level increases, parents' health-related quality of life significantly improves. However, once the education level reaches a certain threshold, the marginal effect on parents\u0026rsquo; HRQoL gradually diminishes. In particular, when children\u0026rsquo;s education level is low, increasing education significantly improves parents\u0026rsquo; health, as higher education is typically associated with stronger economic support, more comprehensive health knowledge, and broader social support resources. However, when children\u0026rsquo;s education level reaches college or higher, the marginal effect on parents\u0026rsquo; health-related quality of life decreases. This may be because, as education levels increase, children may migrate to urban areas, and the reduced face-to-face support from children negatively impacts parents\u0026rsquo; mental health, subsequently affecting their overall health.\u003c/p\u003e \u003cp\u003eThe finding of this inverted U-shaped relationship is consistent with some conclusions in existing literature. One study pointed out that, as parents enter old age, the absence of emotional support and daily care from children significantly weakens the psychological health benefits that higher education brings to rural parents, thereby affecting their health levels\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e. Other studys highlighted that children\u0026rsquo;s increased education level can improve parents' health through economic support and health knowledge transmission. However, as children's education level rises, especially when they migrate to urban areas, the separation between children and parents may lead to negative effects on parents' health with the diminishing marginal effect observed in our study\u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e. Jia also pointed out that there is an inverted U-shaped relationship between years of education and family health, meaning that rural residents gain limited health benefits from higher education, and the health returns for highly educated individuals gradually diminish\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, unlike previous studies that proposed a linear relationship where an increase in children\u0026rsquo;s education level significantly improves parents\u0026rsquo; health-related quality of life\u003csup\u003e[\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e ,our study revealed pattern in the influence of education on parents\u0026rsquo; health. In rural areas, the improvement in children\u0026rsquo;s education level not only affects parents' health through better health behaviors, increased economic support, and social capital accumulation, but is also influenced by factors such as the spatial separation between children and parents and the reduction of intergenerational support. As children\u0026rsquo;s education level becomes higher, the positive effects gradually weaken, likely due to changes in work and living arrangements resulting from urban-rural differences, increased life pressures, and reduced intergenerational interaction. Hence, \u003cb\u003ehypothesis H\u003c/b\u003e\u003csub\u003e\u003cb\u003e1a\u003c/b\u003e\u003c/sub\u003e is supported.\u003c/p\u003e \u003cp\u003eFor the human capital of the next generation, research indicates a significant positive relationship between the health levels of the offspring and the health-related quality of life of the parents. This aligns with previous studies\u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e, which suggest that when the next generation possesses high levels of health capital, it translates to better employment opportunities and higher income levels, enabling them to provide economic support to their parents and alleviate their financial burdens, thus improving the parents' quality of life. Alternatively, when the offspring have higher health capital, it reflects their better health status, reducing the care and support required from the parents, thereby easing the parents' psychological burden and stress. Therefore, \u003cb\u003ehypothesis H\u003c/b\u003e\u003csub\u003e\u003cb\u003e1b\u003c/b\u003e\u003c/sub\u003e is supported.\u003c/p\u003e \u003cp\u003eThe findings of this study underscore the critical role of the offspring's health in the overall family well-being, highlighting the importance of enhancing health education and capacity building for the younger generation in family health management and policy-making. Furthermore, in the mediation effect test, the perception of social support strengthens the positive impact of the offspring's education on the parents' health-related quality of life. This is consistent with previous research, which indicates that elderly individuals who receive economic and emotional support from their children are more likely to adopt positive health behaviors, leading to improved physical and mental health \u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. For the relationship between offspring health and parental health-related quality of life, perceived social support acts as a full mediator. Specifically, the health of the offspring can improve the parents' quality of life by enhancing their social support, which is in line with prior studies. As a core component of elderly individuals' social relationships, intergenerational support from the next generation can significantly strengthen emotional closeness with elderly parents, boost positive emotions, maintain physical and mental health, and ultimately improve life quality\u003csup\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/sup\u003e. Hence, \u003cb\u003ehypothesis H\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e is confirmed.\u003c/p\u003e \u003cp\u003eIn the moderation effect test of digital health literacy, it was found that digital health literacy did not moderate the relationship between offspring education and the health-related quality of life of parents. This may be due to several factors. On one hand, the human capital of offspring education may influence the parents' health-related quality of life through indirect pathways, such as enhancing social support, which has already been empirically validated in the mediation effect test described earlier in this study. These pathways may not necessarily depend directly on digital health literacy. On the other hand, the majority of the parents surveyed in this study are elderly individuals aged 60 and above, residing in rural areas, with relatively low educational levels. Many of these parents lack the motivation to actively engage in learning or the corresponding ability to apply digital health technologies. As a result, digital health literacy did not have the expected moderating effect between offspring education and the health-related quality of life of the parents \u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRegarding the relationship between offspring health human capital and the health-related quality of life of parents, digital health literacy played a significant negative moderating role, which is also consistent with previous research. Specifically, when parents have higher digital health literacy, they are more likely to actively use digital networks to obtain health information to manage and improve their health status, thereby reducing reliance on their children. In this case, the additional contribution of the offspring's health capital to the parents' health-related quality of life is relatively small\u003csup\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e. Alternatively, distorted information and misinformation may lead to biased health perceptions and incorrect health behaviors among parents\u003csup\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e. Furthermore, parents with a certain level of health information literacy tend to choose to believe health viewpoints that favor their own well-being, which may lead to conflicts in health management opinions or strategies between the offspring and parents, thereby impacting the parents' health-related quality of life\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/sup\u003e. Therefore, \u003cb\u003ehypothesis H\u003c/b\u003e\u003csub\u003e\u003cb\u003e3\u003c/b\u003e\u003c/sub\u003e is supported.\u003c/p\u003e \u003cp\u003eThe lack of significant impact from variables such as parental education level, health insurance, smoking, drinking, children's age, children's gender, number of children, and family type on the health utility value of parents may be attributed to several factors. First, the differences in sample characteristics could play a role. The study primarily involves a rural population, and the parents in the sample generally have lower education levels. This may limit the impact of variables like education and health insurance. In this context, the health utility value of parents may be more influenced by socio-economic and emotional support rather than by education level or health insurance alone.\u003c/p\u003e \u003cp\u003eSecond, there may be interactions between health behaviors and the social environment. For instance, the impact of behaviors like smoking and drinking could be influenced by multiple factors, such as family interactions. Especially in rural areas, the health status of parents is often more impacted by community and family support, which may diminish the independent effect of these variables.\u003c/p\u003e \u003cp\u003eAdditionally, factors such as children's gender, age, and family type may, in some cases, have potential effects on the health utility value of parents. However, these effects may be moderated by other variables (e.g, family economic status), which results in their lack of significance in the statistical model.\u003c/p\u003e \u003cp\u003eIn summary, based on the above research findings, the study proposes the following recommendations: Firstly, it is important to strengthen educational support for the next generation in rural areas and optimize intergenerational support mechanisms. While promoting rural education development, the government should also focus on the intergenerational support system between parents and children to prevent a decline in parents' health and well-being due to the migration of children. For example, rural community support networks can be established to foster emotional connections between children and parents, ensuring that parents continue to receive necessary health support even after their children migrate.\u003c/p\u003e \u003cp\u003eSecondly, improving the health level of the next generation is crucial for promoting family health management. The health of children has a significant positive impact on the health-related quality of life of parents. The government should pay more attention to the health of children, particularly in rural areas, and promote health education and health promotion programs to enhance the health status of the next generation, thereby indirectly improving the health of parents.\u003c/p\u003e \u003cp\u003eSimultaneously, it is essential to actively build a multi-level social support network. Perceived social support plays a significant mediating role between the human capital of children and the health-related quality of life of parents. The government should strengthen the development of social support networks in rural communities, encourage intergenerational interaction, and improve parents' perception of social support. For example, community activities and volunteer services can be organized to enhance the social support networks for rural parents, ultimately improving their health-related quality of life.\u003c/p\u003e \u003cp\u003eLastly, there is a need to enhance digital health literacy among rural parents. The negative moderating role of digital health literacy between children's health capital and parents' health highlights the need for the government to provide training on digital health literacy for rural parents, improving their ability to access health information through digital technologies. For example, community health lectures and digital skills training can be organized to help rural parents better utilize the internet for health information, reducing their reliance on their children.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThis study yields three main conclusions: (1) There is an inverted U-shaped relationship between offspring's educational human capital and parental health-related quality of life, while a linear positive correlation exists between offspring's health-related human capital and parental health-related quality of life. Moreover, in terms of marginal effects, offspring's health-related human capital has a greater impact on parental health-related quality of life compared to educational human capital. (2) Regarding the mediating effect of perceived social support, it plays a mediating role in the relationship between offspring's human capital endowment and parental health-related quality of life. (3) Concerning the moderating effect of digital health literacy, it does not significantly moderate the relationship between offspring's educational human capital and parental health-related quality of life. However, it plays an important moderating role in the mediating pathway of educational level influencing perceived social support. Additionally, digital health literacy negatively moderates the relationship between offspring's health-related human capital and parental health-related quality of life and also exerts a certain moderating effect in the pathway where offspring's health status influences perceived social support.\u003c/p\u003e \u003cp\u003eBased on this, the study provides three meaningful conclusions by thoroughly examining the impact of children's human capital on the health-related quality of life of elderly parents in rural areas. However, it is important to note that this study employs cross-sectional data, which, while revealing correlations between variables, cannot definitively establish causal relationships. Therefore, we are unable to conclusively determine whether improvements in children's human capital directly lead to improvements in the health of elderly parents or whether other unmeasured potential variables are at play. Additionally, the study lacks experimental controls, which may result in the influence of external confounding variables on the findings. Future research could adopt a longitudinal design to establish clearer causal links, thereby enhancing internal validity.\u003c/p\u003e \u003cp\u003eMoreover, the data in this study is sourced from rural areas in three different provinces, which provides some representativeness; however, the results are only applicable within a specific geographic context and may not fully represent rural areas nationwide. Factors such as regional disparities, economic development levels, and cultural backgrounds could affect the relationship between children's human capital and elderly parents' health-related quality of life. Future studies should expand the sample scope to include more diverse regions and socio-economic backgrounds, conducting cross-regional and cross-cultural comparative research.\u003c/p\u003e"},{"header":"6. Limitations","content":"\u003cp\u003eFirst, when measuring digital health literacy, due to the limitations of the survey, this study used a single-item indicator to assess the digital health literacy of elderly parents. This may not fully capture the complexity of digital health literacy. While this indicator reflects elderly parents' ability to access health information in some aspects, future research could utilize digital health literacy scales to obtain more accurate results.\u003c/p\u003e \u003cp\u003eSecond, there are potential omitted variables. This study focuses on analyzing children's educational and health-related human capital but overlooks other important factors that may influence elderly parents' health, such as family economic status and community healthcare resources. These omitted variables could affect the accuracy and comprehensiveness of the findings. Future studies should consider these factors to refine the theoretical framework.\u003c/p\u003e \u003cp\u003eIn conclusion, this study provides valuable insights into the impact of children's human capital on elderly parents' health-related quality of life, contributing to the exploration of healthy aging and intergenerational health transmission. However, the limitations in the research design remind us to exercise caution when interpreting the results. Future studies need to address these limitations by employing more rigorous experimental designs, controlling for a broader range of variables, and conducting cross-regional and cross-cultural comparisons to further validate and expand the conclusions of this study.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cem\u003eHRQoL\u003c/em\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealth-Related Quality of Life\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Helsinki Declaration. The study was conducted in accordance with the Declaration of Helsinki and approved by the National Natural Science Foundation of China (Project Approval No.72074084). Participants voluntarily participated, were\u003c/p\u003e\n\u003cp\u003einformed about the survey\u0026rsquo;s purpose, answer methods, and precautions, and signed informed consent forms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received by the National Natural Science Foundation of China (Project Approval No. 72074084).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, X.Z, C.J ,P.R,; methodology, C.J; data curation, C.J; writing\u0026mdash;original draft preparation, P.R, C.J; writing\u0026mdash;review and editing, P.R, J.J, J.X, M.C; supervision, X.Z; project administration, X.Z. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all the participants who participated in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAn explanation of why your manuscript should be published in \u003cem\u003eBMC Public Health\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFocusing on intergenerational health support mechanisms in the context of aging in rural China, this study combines family systems theory and digital inclusion perspectives to explore the impact of offspring human capital (education and health) on the health-related quality of life of rural fathers. The choice to submit the manuscript to \u003cem\u003eBMC Public Health\u003c/em\u003e was based on the following reasons.\u003c/p\u003e\n\u003cp\u003eFirst, the study focuses on the health-related quality of life (HRQoL) of rural middle-aged and elderly fathers, and explores the intergenerational transmission of offspring human capital, which is a direct response to \u003cem\u003eBMC Public Health\u0026apos;s\u003c/em\u003e focus on the issues of \u0026ldquo;health interventions in aging societies\u0026rdquo; and \u0026ldquo;health inequalities in families\u0026rdquo;. This directly responds to \u003cem\u003eBMC Public Health\u0026apos;s\u003c/em\u003e focus on \u0026ldquo;health interventions in an aging society\u0026rdquo; and \u0026ldquo;family health inequalities\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eSecond, the study innovatively introduces \u0026ldquo;digital health literacy\u0026rdquo; as a moderator variable, revealing the complexity of intergenerational health resource transmission in the context of digitization, which is highly consistent with \u003cem\u003eBMC Public Health\u0026apos;s\u003c/em\u003e focus on the theme of \u0026ldquo;digital technology for health equity\u0026rdquo;. This is highly consistent with BMC Public Health\u0026apos;s focus on the theme of \u0026ldquo;digital technology for health equity\u0026rdquo;.\u003c/p\u003e\n\u003cp\u003eIn addition, based on Chinese rural data, the study analyzes the health challenges faced by the elderly in low- and middle-income countries with significant urban-rural disparities and accelerated aging, and provides universal conclusions for developing countries, which is in line with \u003cem\u003eBMC Public Health\u0026apos;s\u003c/em\u003e mission of promoting \u0026ldquo;global health equity\u0026rdquo;. In conclusion, this study not only fills the research gap in the field of intergenerational health transmission, but also provides a scientific basis for the global healthy aging strategy through a digital perspective.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAn explanation of any issues relating to journal policies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study complies with the journal policy of \u003cem\u003eBMC Public Health\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA declaration of any potential competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no potential conflicts of interest in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfirmation that all authors have approved the manuscript for submission\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have fully reviewed and approved this manuscript for submission to \u003cem\u003eBMC Public Health\u003c/em\u003e, ensuring that all content in the manuscript is accurate and agreeing to make changes and improvements as required by the journal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfirmation that the content of the manuscript has not been published, or submitted for publication\u0026nbsp;elsewhere\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript is an original study and has not been published in or submitted to other journals or platforms. All data and analysis results were independently performed by our research team and did not involve any form of duplicate submissions or plagiarism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIf you are submitting a manuscript to a particular special issue, please refer to its specific name in your covering letter\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study is not planned to be submitted to a specific special issue.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgeing and health[EB/OL]. [2024-08-15]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/china/zh/health-topics/ageing\u003c/span\u003e\u003cspan address=\"https://www.who.int/china/zh/health-topics/ageing\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang P. 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Psychol Bull. 2009;135(4):555\u0026ndash;88. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1037/a0015701\u003c/span\u003e\u003cspan address=\"10.1037/a0015701\" 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":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6299719/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6299719/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Background: China's rural population is aging and facing challenges in geriatric health management. Under the family-centered health promotion model, existing studies have mostly focused on the unidirectional health impact of the father's generation on the children's generation and the role of education and single human capital, neglecting the feedback mechanism of the children's multidimensional human capital (education and health) on the health of the father's generation. Based on the family system theory and field research data, this study systematically analyzes the role of offspring human capital on the quality of life in old age, and provides a scientific basis for the development of intergenerational health support policies. Methods: Using field survey data collected from Chongqing, Gansu, and Zhejiang between July and August 2023, the study employs linear regression to analyze the relationship between offspring human capital and parental HRQoL. The mediating role of perceived social support is tested via the bootstrap method, and the moderating role of digital health literacy is analyzed using moderation regression. Results: The average parental health utility value (0.90±0.18) is lower than that of off-spring (0.97±0.09), indicating generally good health among respondents. Offspring educational human capital exhibits an inverted U-shaped relationship with parental HRQoL, while offspring health human capital is positively correlated (β=0.3560, p\u003c0.001). Perceived social support mediates this relationship (β=0.0085, p\u003c0.001), ac-counting for 10.89% and 6.78% of the effect. Digital health literacy negatively moderates the relationship between offspring health human capital and parental HRQoL, but no significant moderation was found in the relationship with offspring educational human capital. Conclusion: Offspring human capital positively influences parental HRQoL, with the effect of health human capital outweighing that of education. Perceived social support serves as a mediator, and digital health literacy moderates the impact of offspring health human capital on parental HRQoL.","manuscriptTitle":"Research on the Impact Mechanism of Offspring Human Capital Endowment on the Health-Related Quality of Life of Rural Fathers from the Perspective of Digital Integration","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 12:48:06","doi":"10.21203/rs.3.rs-6299719/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"eda2ac5d-51e4-419e-85d3-5c857b27fa0a","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-30T13:12:36+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 12:48:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6299719","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6299719","identity":"rs-6299719","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}