Can Skip-generation Caregiving Improve the Quality of Life for the Elderly?

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Feng Chen, Ruixin Gao, Lihua Ma, Linyi Qian, Lianxing Yang, Zhixin Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4387499/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: In the context of Chinese society, where skip-generation caregiving is a prevalent form of childcare, understanding its implications for the well-being of caregivers, especially concerning cognitive abilities, is imperative. This caregiving arrangement not only alleviates reproductive pressures on younger parents but also promotes societal integration and addresses the challenges posed by an aging population. Despite its benefits, the impact of this form of caregiving on the quality of life of elderly individuals particularly in terms of cognitive function, warrants thorough investigation Objective: To investigate the impact of skip-generation caregiving on the cognitive abilities of the elderly, this study will focus on the quality-of-life impacts and the underlying mechanisms involved. Methods: Utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) for the years 2012, 2015, and 2018,this study constructs an econometric model to assess the relationship between skip-generation caregiving and the cognitive abilities of elderly individuals. Logistic regression models were employed to elucidate the mechanisms through which caregiving influences cognitive outcomes. Results: Regressions reveal a positive correlation between skip-generation caregiving and improved cognitive abilities in caregivers. Furthermore, a moderate increase in caregiving intensity is associated with sustained cognitive levels. Economic prosperity amplifies the positive effects of caregiving on cognitive health, although the benefits diminish with the caregiver's advancing age. The study highlights three main pathways through which caregiving benefits cognitive function: a reduction in depressive symptoms, increased social interactions, and enhanced intergenerational economic support. Conclusions: Skip-generation caregiving has been shown to be beneficial for the cognitive health of elderly individuals, with economic status and the economic status of the caregiver and the intensity of caregiving intensity playing significant roles in the extent of these benefits. Tailoring support to meet the specific needs of caregivers is crucial for maximizing the preventive effects against cognitive decline. This research offers valuable insights for policy-making process of developing countries. aging skip-generation caregiving cognition 1. Introduction With the rapid development of the economy and continuous changes in the population structure, the issue of aging in China has become increasingly prominent. According to the 2023 National Report on the Development of Aging Affairs, by the end of 2023. Currently, the proportion of the elderly population aged 60 and above has surpassed 20%. Around 2035, China is expected to enter the stage of severe aging. Meanwhile, China's average life expectancy has steadily increased, from 71.4 years in 2000 to 78.2 years in 2021, indicating that the physical condition of the retired elderly population remains relatively good, with potential to contribute to their families or society. In addressing the challenges of an aging demographic, the emphasis has been placed on the advancement of the 'Healthy China initiative' as a proactive approach to counteract the impacts of population aging. As life expectancy increases, so does the risk of physical and cognitive disabilities among the elderly [ 1 ], raising concerns about their quality of life. The cognitive abilities of the elderly significantly affect their quality of life. The "Alzheimer's Patient Needs Insight Report" released in 2023 points out that Alzheimer's patients in China are mainly elderly but show a trend towards younger ages. The "Healthy China Action" plan aims to reduce the incidence of dementia among individuals aged 65 and above by 2030, Achieving this objective necessitates the continuous identification and implementation of effective strategies to prevent cognitive deterioration. The principle of ‘use it or lose it’ suggests maintaining good cognition requires elderly people to remain mentally active and socially connected after retirement. Traditionally, Chinese extended families have tight-knit relationships, with members mutually providing caregiving and support. The skip-generation caregiving model, where elderly family members care for their grandchildren, is a common practice that leverages the labor resources of the elderly to facilitate their participation in social activities, potentially slowing cognitive decline and improving their life quality in old age. Data from the China Health and Retirement Longitudinal Study (CHARLS) show that 37.87% of families in China engage in skip-generation caregiving, with grandparents and their partners spending an average of 44.61 hours per week to childcare. This model not only mitigates the risk of the elderly experiencing an empty nest syndrome but also benefits their physical, mental, and cognitive health [ 2 ]. Despite its advantages, skip-generation caregiving can significantly alter the social relationships of the elderly, introducing challenges. The "China Migration Development Report 2016" shows that nearly 18 million of China's aging migrant population, 43% of whom relocate to provide childcare, struggle to adapt to new environments, potentially leading to cognitive decline. Hence, the actual impact of skip-generation caregiving on the cognitive status of the elderly remains unclear. This paper seeks to empirically explore the effect of skip-generation caregiving on the cognitive abilities of the elderly. It distinguishes itself from previous studies in several key ways: First, it employs scientific indicators to measure cognitive abilities, relying on the accuracy of responses to specific questions instead of self-assessment, thus ensuring greater rigor in the study. Secondly, it acknowledges that skip-generation caregiving profoundly impacts the social environment, mental state, and economic resources of the elderly. These three aspects are integrated as mediating variables in the model, thereby enriching the practical relevance of the findings. Thirdly, in alignment with the objectives of the ‘Healthy China initiative’ and its proactive approach to aging, this paper verifies the impact of skip-generation caregiving behavior on the quality of life of the elderly based on the China Health and Retirement Longitudinal Study, providing a more scientific analysis of the impact mechanisms. Additionally, it conducts a heterogeneity analysis based on age and economic status and performs robustness tests on the results, making the conclusions more accurate and deepening the understanding of the mechanisms by which skip-generation caregiving affects the cognitive abilities of the elderly. This work represents an insightful case study from a developing country, significantly enriching the global discourse on intergenerational caregiving dynamics. 2. Literature Review Due to tight intergenerational bonds and limited childcare facilities, caregiving by grandparents has become a prevalent practice in China. A significant number of scholars have explored the effects of this caregiving model on elderly lives, focusing their research on its impact on grandparents' living conditions, mental health, and self-awareness of their needs. Yet, the academic community has not reached a consensus regarding the impact of such caregiving on the cognitive abilities of older adults. Caring for grandchildren significantly transforms the lives of elderly individuals by increasing their physical activity and strengthening bonds with their children, leading to a more engaging lifestyle. Studies by Bonsang et al. [ 3 ] and Atalay et al. [ 4 ] indicate that retirement can negatively impact the cognitive functions of older adults. However, engaging in grandparenting activities can enhance their participation in the labor force and slow cognitive decline. Arpino and Bordone [ 5 ] posited that caregiving activities by grandparents can escalate intellectual engagement, hence preserving their analytical and memory skills and preventing cognitive deterioration. This research also found that grandparents who engage in caregiving activities demonstrate notable improvements in linguistic fluency. In China, many "floating elders" who move to live with their children in their later years receive significant emotional support from their families. Engaging in grandparenting markedly increases interactions between older adults and their children [ 6 ], enhancing grandparents' sense of well-being and supporting cognitive health. However, although the studies acknowledge positive effects, they often oversimplify the mechanisms through which grandparenting influences cognitive abilities. Commonly, they suggest that caregiving offers additional mental stimulation, thereby helping to prevent cognitive decline. Although this effect is evident, it does not encompass all contributing factors. Furthermore, grandchild care can lead to psychological stress and depression in grandparents, with these adverse emotions varying based on social contexts. In places like the United States [ 7 ] and Kenya [ 8 ], caregiving is seen as a major stressor for grandparents, potentially leading to depression, anxiety, and cognitive impairments. Ates [ 9 ], analyzing data from the German Ageing Survey (DEAS), discovered that caregiving has a modestly positive impact on the physical and psychological health of German elders. In China, caregiving often positively affects older adults' mental health. Research by Xu [ 10 ] and Choi and Zhang [ 11 ] suggests that grandparenting can sustain positive mental health in Chinese elders, also reducing the likelihood of chronic conditions like hypertension. Age is also one of the primary factors affecting the physical and mental health of elderly individuals in real life. Existing research on the role of age in the process of grandparenting is somewhat cursory, lacking a detailed investigation into how age variations affect this dynamic. This article aims to conduct a heterogeneity analysis based on age, thereby filling this gap in the literature. Some studies have pointed out that caregiving impacts the promptness of medical care among the elderly, yet effect of this influence remains contentious. Research by Baker and Silverstein [ 12 ]showed that grandmothers who provide care are more diligent about undergoing health screenings and vaccinations. Di Gessa et al. [ 13 ], through their analysis of European elder retirement data, noted that grandparenting enhances the financial and temporal support from children, encouraging elders to monitor their health closely. Wang et al. [ 14 ] argued that extended caregiving might lead to a neglect of the grandparents' own health needs. This variance in findings could stem from different levels of caregiving intensity; a lower intensity may foster intimate relationships and health vigilance, whereas a higher intensity of caregiving could overshadow the grandparents' health issues. This paper will specifically examine the effects of caregiving intensity on these dynamics. 3. Theoretical Analysis and Research Hypotheses The cognitive decline faced by elderly individuals can significantly impact their physical and mental health, as well as their ability to live independently. To decelerate this decline, scholars globally have investigated the factors that influence cognitive functions. Present discussions have identified five primary factors affecting the cognitive abilities of the elderly: the factors influencing the cognitive abilities of the elderly can primarily be summarized into five aspects: personal lifestyle, physical and mental health, degree of social participation, and intergenerational economic support. Personal lifestyle choices, such as smoking, alcohol consumption, and engagement in leisure activities, have a direct impact on cognitive functions. Liu et al. [ 15 ] analyzed the cognitive decline trajectory of elderly individuals, finding that moderate sleep, regular exercise, and dietary habits could significantly mitigate cognitive deterioration. Both mitigate cognitive deterioration have a negative impact on cognitive abilities. Lu et al. [ 16 ] explored the factors contributing to dementia in older adults, discovering that consistent physical exercise and work protect brain and reduce dementia risk. The physical and mental health of elderly individuals impact their cognitive abilities through different mechanisms. Reitz et al. [ 17 ] argued that the coexistence of hypertension and hyperlipidemia indirectly leads to neuronal function impairment, thus cognitive decline. Moreover, improved hearing can decelerate cognitive decline [ 18 ]. Negative emotions including depression and anxiety negatively impact cognitive functions and indirectly lower cognitive abilities through influencing individual behavior. Gatchel et al. [ 19 ] suggested that depressed elderly individuals are more likely to develop dementia, with depression potentially being a precursor to dementia. Coutinho et al. [ 20 ] found that severe depression accelerates memory decline in the elderly, severely negatively affecting their cognitive functions. A higher degree of social engagement encourages the acquisition of new knowledge among elderly individuals, thereby protecting their cognitive abilities. Hou et al. [ 21 ] found that elderly individuals active in social activities have better memory, making social participation a protective factor for cognitive abilities. Song et al. [ 22 ] studied the living environments of elderly Americans, finding those residing in densely populated communities exhibit higher cognitive abilities, likely due to varied degrees of social engagement in different community settings. Economic support from adult children improves the living conditions of the elderly, thus influencing their cognitive functions. Mani et al. [ 23 ] found that the economic status of elderly individuals significantly impacts their cognitive abilities in later life, with economically disadvantaged elderly individuals often also having poor nutrition and lower education levels. Moreover, concerns about economic conditions can hinder individual cognitive function [ 24 ]. Sharifi et al. [ 25 ] investigated the potential link between intergenerational relations and cognitive performance among elderly individuals in East Asian countries, finding that frequent intergenerational economic exchanges help maintain cognitive health among the elderly. Based on the above analysis, this article proposes the following hypotheses: Hypothesis 1 Through caregiving for grandchildren, grandparents may experience enhanced self-worth, thereby obtaining self-identity and reducing loneliness after retirement. Grandparenting indirectly bolsters their cognitive abilities by alleviating depression. Hypothesis 2 Grandparenting after retirement strengthens social ties for the elderly, encouraging them to participate more in social activities and increase daily exercise. Grandparenting has a positive impact on their cognitive abilities by enriching the complexity of their social networks. Hypothesis 3 Families engaged in grandparenting have closer intergenerational ties and higher levels of intergenerational economic support, providing elderly individuals with better health monitoring and medical environments, positively affecting their cognitive abilities. 4. Research Design and Data Description 4.1 Model Setup Baseline Regression This paper employs a two-way fixed effect, establishing the econometric model as follows: $${Y}_{i}={\alpha }_{0}+{\alpha }_{1}{C}_{i}+{\alpha }_{2}{X}_{i}+{\delta }_{c}+{\delta }_{t}+{\epsilon }_{i}$$ The dependent variable \({Y}_{i}\) represents the cognitive abilities of the elderly population. The core explanatory variables \({C}_{i}\) , include "whether to perform skip-generation caregiving" and "the intensity of skip-generation caregiving". Control variables \({X}_{i}\) are incorporated, and the parameter of interest \({\alpha }_{1}\) represents the impact of explanatory variables on the dependent variable. \({\delta }_{c}\) represents unchanging regional fixed effects, \({\delta }_{t}\) represents survey year fixed effects, and \({\epsilon }_{i}\) is the random error term. Mechanism Analysis The mechanism analysis follows the approach of Jiang [ 26 ] and Yi et al. [ 27 ], utilizing mechanism variables that have a proven causal relationship and are temporally and logically close as mediating variables, rather than formal causal inference steps. This paper conducts regression analyses of psychological health status, social relationship complexity, and intergenerational economic support on the presence of skip-generation caregiving to investigate the mechanisms involved. $${M}_{i}={\beta }_{0}+{\beta }_{1}{C}_{i}+{{\beta }_{2}X}_{i}+{\delta }_{c}+{\delta }_{t}+{\epsilon }_{i}$$ The mechanism variable \({M}_{i}\) includes psychological health status, social relationship complexity, and intergenerational economic support as model mechanism variables. 4.2 Data Source and Processing The data for this study are sourced from the China Health and Retirement Longitudinal Study (CHARLS), which focuses on Chinese individuals aged 45 and above. The survey encompasses 28 provinces, 150 county units, 450 village units, and roughly 17,000 individuals across 10,000 households. The data contain personal basic information, physical health status, cognitive and depression conditions, income, and property, etc., closely aligning with the research objectives of this study. This comprehensive database was selected to provide robust data support for our analysis. For this paper, mixed cross-sectional data from the years 2012, 2015, and 2018 were utilized. Samples lacking children or grandchildren and individuals older than 85 years were excluded, yielding 9,814 valid observations. 4.3 Variable Selection and Description 4.3.1 Dependent Variable: Cognitive Ability of Elderly People Cognitive abilities are assessed using specific test scales, with scores assigned accordingly. The test, conducted via questionnaire, evaluates various cognitive domains including temporal orientation, attention and calculation, spatial abilities, language proficiency, and both immediate and delayed memory functions [ 28 ]. For categorical questions, each correct answer is awarded 1 point. For quantitative questions, points are awarded based on the number of correct responses, while refusals or failures to answer are scored as 0. The maximum possible score for the cognitive ability test section is 80 points. The full score for the cognitive ability test part is 80 points, with higher scores indicating higher levels of cognitive ability. 4.3.2 Core Explanatory Variables: Whether to Perform skip-generation caregiving and the Intensity of skip-generation caregiving "Whether to perform skip-generation caregiving" and "the intensity of skip-generation caregiving" are selected as core explanatory variables. The survey inquires of respondents with grandchildren under the age of 16 whether they or their spouse have spent time in the past year caring for their grandchildren, with the possible responses being "yes" or "no". If skip-generation caregiving behavior exists, the value is 1; otherwise, it's 0. The intensity of skip-generation caregiving is measured by two dimensions: the number of grandchildren cared for and the weekly hours spent on skip-generation caregiving. According to the method applied by Flamion [ 29 ], in cases where elderly family members do not reside with their grandchildren but still engage in skip-generation caregiving, the average time spent on such caregiving is calculated. The variables thus capture the actual number of grandchildren under 16 cared for and the weekly hours dedicated to skip-generation caregiving. 4.3.3 Mechanism Variables: Psychological Health Status, Social Relationship Complexity, and Intergenerational Economic Support Firstly, the degree of depression is selected as a measure of the psychological health status of elderly people. CHARLS survey utilizes the CESD-10 scale to measure symptoms of depression[ 30 ], consisting of 10 items each rated between 0–3 according to the frequency of the symptoms experienced. A higher total score indicates more severe depressive symptoms, with scores of 10 or above classified as indicative of depressive symptoms[ 31 ]. Scores ≥ 10 are defined as having depressive symptoms, with an overall Cronbach's α coefficient of 0.802.Secondly, in line with prior research, the complexity of social relationships and intergenerational economic support are identified as mechanism variables that influence cognitive ability, reflecting how these factors potentially affect cognitive functions in the elderly. 4.3.4 Control Variables To address the issue of endogeneity arising from omitted variables, the model incorporates a comprehensive set of control variables. These variables are categorized across individual, family, and city/regional levels to ensure a thorough analysis. At the individual level, control variables include Age, square of age, gender, marital status, education level, self-rated health status, intensity of daily exercise, degree of chronic illness, sleep duration, lifestyle habits, personal pension. At the family level, variables encompass Total income, net assets, household size, household consumption expenditure, child dependency ratio, elderly dependency ratio, homeownership, debt ownership, and whether the household is in a rural area. Additional city and regional level control variables include The per capita GDP of the region, local fiscal budget, local fiscal spending on science and education, the share of secondary industry in GDP, the share of tertiary industry in GDP, and categorical variables for eastern, western, and central regions. 5. Empirical Analysis 5.1 Baseline Regression Baseline Analysis: The Impact of skip-generation caregiving on the Cognitive Abilities of Elderly People In the baseline regression, cognitive ability is used as the dependent variable, with the presence of skip-generation caregiving as the core explanatory variable. Personal characteristic control variables and family characteristic control variables are progressively introduced into the regression for estimation. Table 1 Regression Results for the Impact of Grandparenting on Cognitive Ability OLS (1) OLS (2) OLS (3) Grandparenting 0.6518*** (0.1565) 0.6981*** (0.1598) 0.5601*** (0.1551) Individual and Household-level Control Variables YES YES Regional-level Control Variables YES Individual Fixed Effects YES YES YES Time Fixed Effects YES YES YES Observations 9814 9814 9814 According to the regression results shown in Table 1 , with the continuous introduction of control variables, skip-generation caregiving has a positive impact on the cognitive abilities of elderly people and is significant at the 1% level of significance. This is consistent with the conclusions drawn in the theoretical summary of this paper. Specifically, skip-generation caregiving leads to an increase of 0.5601 in the scale score, which is about a 15% improvement. This enhancement likely stems from the direct increase in daily physical activity among elderly individuals due to skip-generation caregiving behavior, the improvement in their level of social participation, and indirectly increasing their sense of self-identity. Such factors collectively foster the physical and mental health of elderly individuals, thereby supporting the maintenance of robust cognitive functions. Baseline Analysis: The Impact of skip-generation caregiving Intensity on the Cognitive Abilities of Elderly People In light of the variations in skip-generation caregiving levels among individuals, this study has refined its approach by substituting the dependent variable with three new measures: the number of grandchildren cared for, the weekly hours spent on skip-generation caregiving, and skip-generation caregiving intensity. Here, skip-generation caregiving intensity is defined as the product of the time spent caregiving and the number of grandchildren cared for. This adjustment is made while retaining the core explanatory variables and control variables as constant. The impact of skip-generation caregiving intensity on the cognitive abilities of elderly individuals and the intrinsic connection of this impact might be that as the intensity of skip-generation caregiving increases, the connection between elderly individuals and their families becomes closer[ 32 ]. This helps reduce depression caused by loneliness and gain more economic support from children[ 33 ]. Additionally, a higher intensity of skip-generation caregiving enhances the interaction between grandparents and society at large. It enriches the complexity of their social relationships, which, in turn, contributes to a reduced risk of cognitive decline. The subsequent sections of this text will delve deeper into the mechanisms by which skip-generation caregiving influences cognitive abilities Table 2 Regression Results for the Impact of Grandparenting Intensity on Cognitive Ability OLS (1) OLS (2) OLS (3) Number of Grandchildren Cared For 0.15*** (0.03416) Weekly Grandparenting Time 0.05588 *** (0.01183) Grandparenting Intensity 0.02253*** (0.004852) Control Variables YES YES YES Individual, Time Fixed Effects YES YES YES Observations 9814 9814 9814 As shown in Table 2 the number of grandchildren cared for, the weekly skip-generation caregiving time, and the skip-generation caregiving intensity have a positive effect on the cognitive function of elderly people, and this positive effect is significant at the 1% level of significance. These results indicate a positive correlation between skip-generation caregiving and the cognitive abilities of elderly people, with an increase in the number of grandchildren cared for and the increase in weekly skip-generation caregiving time strengthening this positive correlation. The intrinsic connection of this impact might be that as the intensity of skip-generation caregiving increases[ 34 ], the connection between elderly people and their families also becomes closer. This helps reduce depression caused by loneliness and gain more economic support from children. Furthermore, a stronger intensity of skip-generation caregiving promotes contact between grandparents and society, increases the complexity of social relationships, thereby reducing the likelihood of cognitive decline. The following text will further explore the mechanisms through which skip-generation caregiving affects cognitive abilities. 5.2 Endogeneity Problem The decline in cognitive abilities among the elderly is influenced not only by personal factors but also by unpredictable external factors, which have a significant impact on individual cognitive capabilities, making it difficult for the model to cover all relevant explanatory variables. There is also an interplay between skip-generation caregiving behavior and cognitive abilities among the elderly. On one hand, engaging in the care of grandchildren allows elderly individuals to learn new skills, potentially delaying cognitive decline. On the other hand, when signs of cognitive impairment become apparent in grandparents, adult children might hesitate to entrust them with the care of grandchildren, decreasing the instances of skip-generation caregiving. This suggests a bidirectional causal relationship, which, along with omitted variables, introduces endogeneity issues into the study. To address this, the use of instrumental variables becomes necessary. Given the complexity surrounding the measurement of cognitive abilities and the various factors influencing them, the selection of appropriate instrumental variables is critical. Some scholars have used the gender of children, the type of children's employment, the presence of grandchildren, and the average caregiving rate in the community as potential instrumental variables for skip-generation caregiving. Following the approach used by Yin and Zhang [ 35 ], this study selects average skip-generation caregiving rate of other respondents in the same city area as the instrumental variable for engaging in skip-generation caregiving: first, the elderly population in the same city has common preferences for skip-generation caregiving behavior and are easily influenced by other elderly people in their regional environment. If the average level of skip-generation caregiving among the elderly population in the same area is higher, then the likelihood of the respondent engaging in skip-generation caregiving increases, thus satisfying the relevance condition of the instrumental variable; second, by excluding the information on whether the respondent themselves is engaged in skip-generation caregiving, the average skip-generation caregiving rate of other elderly people in the same area does not directly affect cognitive ability, avoiding correlation with the error term and satisfying the exogeneity condition of the instrumental variable; third, this method of constructing instrumental variables has been widely used in many literatures and has achieved good estimation effects. Table 3 Addressing Endogeneity 2SLS 2SLS 2SLS Grandparenting 436.07*** (93.45) Number of Grandchildren Cared For 374.66*** (99.46) Weekly Grandparenting Time 7.156*** (2.279) Instrumental Variable (IV) Status *** *** *** First-stage F-value 68.76 62.06 36.41 Observations 9814 9814 9814 9814 9814 9814 The estimation results presented in Table 3 illustrate that in the first stage of the two-stage least squares (2SLS) regression, as shown in columns (1), (3), and (5), the impact of the instrumental variable on the likelihood of engaging in skip-generation caregiving is significant, positive, and associated with a large F-value. This finding aligns with the prior analysis and indicates that the study does not suffer from the issue of a weak instrumental variable, which can undermine the reliability of 2SLS estimates. When comparing the Ordinary Least Squares (OLS), ordered probit, and 2SLS estimation methods, the coefficient values derived from the second stage of the 2SLS are notably larger than those obtained through the first two methods. However, the sign direction and the fundamental conclusions drawn from these coefficients remain consistent across all methods. This suggests that while the 2SLS method yields stronger associations between skip-generation caregiving and cognitive abilities of the elderly, it fundamentally supports the same underlying relationship as identified by the simpler OLS and ordered probit analyses. This reinforces the validity of the findings regarding the positive impact of skip-generation caregiving on the cognitive functions of elderly individuals, while also highlighting the importance of addressing potential endogeneity through the use of instrumental variables. 5.3 Heterogeneity Analysis The discussion thus far has largely concluded that skip-generation caregiving positively impacts cognitive abilities. In practical terms, age and economic status significantly influence the cognitive functions of elderly individuals. It is widely acknowledged that, within a certain range, cognitive abilities tend to decline with age; Conversely, elderly individuals with higher economic levels have access to better medical conditions, reducing the risk of cognitive decline. To determine whether the effect of skip-generation caregiving on cognitive abilities differs across various backgrounds, the subsequent sections will undertake a heterogeneity analysis, examining the influence from the perspectives of economic level and age. This analysis aims to uncover nuanced insights into how different factors may modulate the relationship between skip-generation caregiving and cognitive health, providing a more comprehensive understanding of the potential benefits and limitations of caregiving across diverse segments of the elderly population. 5.3.1 Economic Level To assess the influence of economic status on the behavior of skip-generation caregiving among the elderly, this study integrates interaction terms between the baseline regression's three core explanatory variables—engagement in skip-generation caregiving, intensity of caregiving, and the number of grandchildren cared for—and economic indicators such as pension income and financial support from children. As shown in Table 4 , the estimated coefficients of the interaction terms between the three skip-generation caregiving variables and pension are significantly positive. This implies that as pension income increases, the beneficial impact of skip-generation caregiving on the cognitive abilities of elderly individuals also grows. Meanwhile, economic support from children to their elderly parents appears to have a positive influence, though this effect does not reach statistical significance. These results indicate that elderly individuals with higher economic status, compared to their lower economic status counterparts, are more capable of leveraging skip-generation caregiving to sustain or even enhance their cognitive functions. This distinction underscores the interplay between economic resources and caregiving activities, suggesting that financial well-being can amplify the cognitive benefits associated with caregiving. The findings highlight the need for supportive policies and interventions that consider the economic backgrounds of elderly caregivers, aiming to maximize the cognitive and overall health benefits of skip-generation caregiving across different economic strata. Table 4 Economic Level Heterogeneity Analysis OLS (1) OLS (2) OLS (3) Grandparenting 1.099*** (0.2633) Grandparenting * Pension 0.001271*** (0.0002003) Grandparenting * Intergenerational Support 0.000007642 (0.00001817) Number of Care Recipients 0.6825*** (0.1843) Number of Care Recipients * Pension 0.0008733*** (0.00015) Number of Care Recipients * Intergenerational Support 0.00006312 (0.0001115) Caregiving Time 0.01603* (0.005014) Caregiving Time * Pension 0.0002686*** (0.00004112) Caregiving Time * Intergenerational Support 0.0000005386 (0.00002979) Other Control Variables YES YES YES Individual, Regional, Time Fixed Effects YES YES YES Observations 9814 9814 9814 5.3.2 Age To address the issue of heteroscedasticity, which often affects the reliability of regression results in cross-sectional data, this paper employs Weighted Least Squares (WLS) regression for the analysis of interaction terms between age and the core explanatory variables related to skip-generation caregiving. The regression results, as shown in Table 5 , indicate that skip-generation caregiving has a significant positive impact on cognitive levels. However, it also shows that cognitive abilities generally decrease as individuals age. The interaction terms between age and the skip-generation caregiving variables yield a negative coefficient, indicating that the beneficial impact of skip-generation caregiving on cognitive levels diminishes with advancing age. These findings suggest that while skip-generation caregiving can act as a buffer against the cognitive decline associated with aging, its effectiveness in counteracting this decline lessens as individuals grow older. This could imply that the cognitive benefits derived from caregiving activities, such as increased social interaction, mental engagement, and physical activity, have a less pronounced impact on older elderly individuals. Consequently, while skip-generation caregiving can provide a meaningful avenue for supporting cognitive health, its potential to mitigate the effects of aging on cognition is not uniform across all age groups, highlighting the need for tailored approaches in caregiving practices and policy formulations to maximize cognitive health benefits for the elderly population at different stages of aging. Table 5 Age Heterogeneity Analysis WLS (1) WLS (2) WLS (3) Age -76.06*** (1.364) -76.31*** (1.283) -82.21*** (1.243) Grandparenting 65.05*** (3.238) Grandparenting * Age -16.86*** (0.8121) Number of Care Recipients 57.22*** (2.394) Number of Care Recipients * Age -14.74*** (0.6043) Caregiving Time 1.571*** (0.005514) Caregiving Time * Age -40.16*** (0.001396) Other Control Variables YES YES YES Individual, Regional, Time Fixed Effects YES YES YES Observations 9814 9814 9814 6. Robustness Tests To ensure the rigor of the research conclusions, this paper conducts robustness tests by replacing the dependent variable from two aspects. Firstly, self-rated memory scores are used instead of cognitive abilities to test the robustness of the regression results. In the valuation of the self-rated memory score variable, this study assigns values sequentially as 5 (excellent), 4 (very good), 3 (good), 2 (fair), 1 (poor), and 0 (very poor) for research. Considering potential minor differences in individual assessments, these ratings are presumed to follow a Poisson distribution to accentuate variability. Secondly, considering that changes in cognitive abilities occur over an extended period, the explanatory power of skip-generation caregiving in the past year on the strength of cognitive abilities is somewhat limited. This paper uses "change in cognitive ability" as the dependent variable for robustness testing. This metric assesses any decline in cognitive scores of the participants relative to their previous evaluation (either in 2015 or 2012), with a decrease denoted by 0 and stability or improvement by 1. Table 6 Robustness Tests Robustness Test 1 Robustness Test 2 Variables Self-Rated Memory Score Change in Cognitive Ability Grandparenting 0.03571* (0.0166) 0.0906** (0.0282) Weekly Grandparenting Time 0.0413*** (0.0111) Control Variables YES YES YES Observations 9814 9814 9684 The data in columns (2) to (4) of Table 6 reveal that both engaging in skip-generation caregiving and the duration of caregiving are positively correlated with self-rated memory scores, exhibiting notable significance. Furthermore, skip-generation caregiving is shown to decrease the likelihood of a decline in cognitive abilities over time. These research results indicate that the conclusions of this paper are fundamentally robust. 7. Mechanism Analysis 7.1 Impact Mechanism: Psychological Health Status The regression results displayed in Table 7 show that skip-generation caregiving significantly reduces depression levels and markedly improves psychological health. This suggests that skip-generation caregiving indirectly boosts cognitive abilities by enhancing psychological health, aligning with Hypothesis (1) of this study. Table 7 Impact Mechanism of Psychological Health Status OLS (1) Ordered Tobit (2) OLS (3) Ordered Tobit (4) Variables (Depression Level) (Depression Level) (Self-rated Psychological Health) (Self-rated Psychological Health) Grandparenting -0.4839*** (0.1889) -0.4771* (0.1897) 0.4239*** (0.1017) 0.4126*** (0.0921) Control Variables YES YES YES YES Observations 9814 9814 9814 9814 7.2 Impact Mechanism: Complexity of Social Relationships The findings presented in Table 8 indicate that participation in skip-generation caregiving significantly enhances the complexity of social relationships. This underscores the role of skip-generation caregiving in fostering social connections, thereby substantiating our theoretical hypothesis (2). According to this hypothesis, the behavior associated with skip-generation caregiving exerts a positive influence on cognitive abilities among the elderly by enriching the complexity of their social interactions. Table 8 Impact Mechanism of Complexity of Social Relationships OLS (1) Ordered Tobit (2) Variables Complexity of Social Relationships Complexity of Social Relationships Grandparenting 0.1366* (0.05862) 0.1363* (0.05861) Control Variables YES YES Observations 9814 9814 7.3 Impact Mechanism: Intergenerational Economic Support In this section, our approach to collecting data on economic factors mirrors that of Böhme et al. [ 36 ]. We consider the economic support provided by children as a mechanism variable, taking into account the direct or indirect household expenses that may increase due to skip-generation caregiving. For instance, as illustrated in the first column of Table 9 , engaging in skip-generation caregiving leads to an increase in household consumption. However, this increase in expenses is relatively minor, and the overall economic comfort level of the household improves. This supports Hypothesis (3), suggesting that indirectly improving cognitive levels through improving a better health monitoring and medical environment positively affects the cognitive abilities of elderly people. Table 9 Impact Mechanism of Intergenerational Economic Support OLS (1) Ordered Tobit (2) Variables Intergenerational Economic Support Intergenerational Economic Support Grandparenting 1259*** (250.9) 2535*** (328.7) Control Variables YES YES Observations 9814 9814 8. Research significance and limitations To comprehensively examine the influence of intergenerational grandparenting on the quality of life among the elderly, it is imperative to access long-term data capturing their engagement in such activities, the extent of involvement, and various facets of their living conditions. This paper opts for the China Health and Retirement Longitudinal Study (CHARLS) and utilizes cognitive function among the elderly as a metric for assessing their quality of life. Intergenerational grandparenting intensity is gauged by both the duration of weekly involvement and the number of grandchildren cared for. Noteworthy is our dataset's inclusion of physical and mental health indices, as well as social standing, enabling us to delve into the underlying mechanisms through which intergenerational grandparenting influences their quality of life, thus providing distinct insights from developing nations. Our findings indicate a significant enhancement in the cognitive function of Chinese elderly through intergenerational childcare practices. Elderly individuals engaged in such care experienced a notable improvement in cognitive function scores, approximately a 15% increase equating to 0.5601. Moreover, within a certain range, an increase in either the number of grandchildren cared for or the weekly time dedicated to intergenerational childcare significantly bolstered elderly cognitive function. These outcomes may stem from heightened physical activity resulting from childcare responsibilities or from strengthened family bonds and social connections fostering improved mental well-being among the elderly. Through heterogeneity analysis, we observed that younger age and higher economic status among the elderly were associated with better mitigation of cognitive decline through grandparenting. Mechanism analysis revealed indirect enhancements in cognitive function among the elderly through reduced depression levels, augmented complexity in social relations, and reinforced intergenerational economic support facilitated by grandparenting. Ultimately, our study underscores the multifaceted impact of grandparenting on the cognitive function of Chinese elderly, ultimately enhancing their quality of life. The implications of our study are significant, offering avenues for retired elderly individuals to sustain their quality of life, aligning with strategies aimed at addressing aging populations [ 37 , 38 ]. Additionally, it suggests leveraging the elderly's contribution to family care, thus alleviating parental pressures and childbirth burdens. For instance, policies encouraging intergenerational childcare participation could lead to a 15% average improvement in cognitive function among elderly individuals, consequently enhancing their overall quality of life. Policy interventions could focus on promoting grandparenting as a means to enhance elderly quality of life, emphasizing its benefits for both the elderly and their families. Establishing an elderly-friendly social environment [ 39 , 40 ], reducing barriers to grandparenting, and facilitating their integration into society are potential strategies. However, the effectiveness of such measures in promoting grandparenting warrants further investigation beyond the scope of this study, highlighting an avenue for future research. For future research directions, this work relies on cognitive ability as a proxy for elderly quality of life. Future studies could enrich our understanding of elderly quality of life by broadening the scope of assessment beyond cognitive ability. Incorporating measures of economic status, physical health, and emotional well-being would provide a more comprehensive understanding of the factors influencing elderly well-being. For limitations, this work primarily relies on cognitive ability to gauge the quality of life among elderly individuals. While cognitive ability undoubtedly plays a significant role, it's also important to acknowledge that factors like economic status, physical health, and overall happiness are equally pivotal in evaluating the quality of life in this demographic [ 41 , 42 ]. Furthermore, the discussion on the influencing mechanism of intergenerational care in this study predominantly focuses on three pathways: mental health, social relations, and intergenerational support. However, the potential impact of intergenerational care on elderly individuals encompasses a broader spectrum. For instance, it can contribute to regularizing the daily routines and activities of the elderly, thereby potentially maintaining cognitive abilities. Recognizing the challenges associated with quantitatively studying additional pathways, this study opts to concentrate on these three influential factors. Additionally, the research methodology employed in the mechanism section begins with identifying correlations between the selected mechanism variables and the cognitive abilities of elderly individuals through literature research and is followed by an exploration of the direct effects of intergenerational caregiving on these variables. At the same time, it's important to acknowledge that such impacts may be more intricate, influenced by numerous exogenous factors. Moreover, this study utilizes mixed cross-sectional data, thus does not aim to capture the longitudinal impact of grandparents' caregiving on individuals throughout the aging process. Due to adjustments in the questionnaire questions in 2012, 2015, and 2018, the cognitive ability scores of the same individual are not directly comparable across different years, precluding the utilization of panel data in this analysis. However, it's worth noting that in real-life scenarios, elderly individuals may commence providing intergenerational care as they age, potentially leading to instances where cognitive decline is halted or even reversed—a topic that remains pertinent and warrants further discussion. 9. Conclusion 1.Historical data show that the Chinese elderly who are raising grandchildren have a significantly higher quality of life, and the increase in the intensity of parenting is conducive to the improvement of the quality of life of the elderly. 2.The higher the economic level of the elderly, the lower the age, and the greater benefits skip-generation caregiving will bring. 3.Encouraging the elderly to carry out skip-generation caregiving may reduce the burden of childbirth on young parents and improve the quality of life of the elderly, which is one of the feasible measures to actively cope with the aging of the population. Declarations Acknowledgements Thank you to all the aged people who participated in the experiment. Authors’ contributions Conceptualization: FC, RG, LM. Data analysis: FC, RG, LQ. Funding acquisition: LM, FC, LQ. Methodology: LY, RG, ZY. Writing original draft: RG, FC, LQ. Writing review & editing: ZY, LM, LY. All authors assisted with writing the article and have approved the citation of their names in the paper. Funding This work was supported by the National Natural Science Foundation of China (12171158), the National Social Science Foundation of China's general project on education (BJA220248), the State Key Program of National Natural Science Foundation of China (71931004) and Fundamental Research Funds for the Central Universities (2022QKT001). Data Availability The data that support the findings of this study are available at https://charls.pku.edu.cn/. Ethics approval and consent to participate All methods were carried out in accordance with relevant guidelines andregulations. The study was approved by the Ethics committee of Henan Normal University (HNSD-2023BS-0628). Informed consent was obtained fromall subjects and/or their legal guardian(s). Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details 1 Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai 200241, China 2 Faculty of Education，East China Normal University，Shanghai 200062, China 3 School of Economics and Management, East China Normal University, Shanghai 200241, China 4 Department of Mathematical Sciences, Ball State University, Muncie 47304, USA References Zeng Y ,Feng Q ,Hesketh T , Christensen K & Vaupel J-W. Survival, disabilities in activities of daily living, and physical and cognitive functioning among the oldest-old in China: a cohort study.The Lancet.2017;389(10079):1619-1629. Gao M, Li Y, Zhang S, Gu L, Zhang J, Li Z& Tian D Does an empty nest affect elders’ health? Empirical evidence from China. International journal of environmental research and public health, 2017, 14(5): 463. Bonsang E, Adam S, Perelman S. Does retirement affect cognitive functioning? Journal of Health Economics. 2012;31(3):490-501. Atalay K, Barrett GF, Staneva A. The effect of retirement on elderly cognitive functioning. Journal of Health Economics. 2019;66:37-53. Arpino B, Bordone V. Does grandparenting pay off? The effect of child care on grandparents' cognitive functioning. Journal of Marriage & Family. 2014;76(2):337-351. Leimer B, van Ewijk R. Are grandchildren good for you? Well-being and health effects of becoming a grandparent. Social Science & Medicine. 2022;313:115392. Ratnakaran B, Shappell AV, Khalid K. Grandparenting and the golden years: Understanding the factors and mental health outcomes of grandparent caregivers in older adults. The American Journal of Geriatric Psychiatry. 2024;32(4):S10. Ice GH, Sadruddin AF, Vagedes A, Yogo J, Juma E. Stress associated with caregiving: An examination of the stress process model among Kenyan Luo elders. Social Science & Medicine. 2012;74(12):2020-2027. Ates M. Does grandchild care influence grandparents’ self-rated health? Evidence from a fixed effects approach. Social Science & Medicine. 2017;190:67-74. Xu H. Physical and mental health of Chinese grandparents caring for grandchildren and great-grandparents. Social Science & Medicine. 2019;229:106-116. Choi S-W, Zhang Z. Caring as curing: Grandparenting and depressive symptoms in China. Social Science & Medicine. 2021;289:114452. Baker LA, Silverstein M. Preventive health behaviors among grandmothers raising grandchildren. Journals of Gerontology - Series B Psychological Sciences and Social Sciences. 2008;63(5):S304-S311. Di Gessa G, Glaser K, Tinker A. The impact of caring for grandchildren on the health of grandparents in Europe: A lifecourse approach. Social Science & Medicine. 2016;152:166-175. Wang X-L, Cheng J, Guo C-Y, Xu X-R. The implications of childcare on grandparents' health self-management in a chinese elderly population. The International Journal of Health Planning and Management. 2020;35(1):280-289. Liu C, Dai X, Li Y, Li H. Lifestyle adjustment: Influential risk factors in cognitive aging. Advances in Experimental Medicine and Biology. 2023;1419:185-194. Lu Y, Bu F-Q, Wang F, Liu L, Zhang S, Wang G, Hu X-Y. Recent advances on the molecular mechanisms of exercise-induced improvements of cognitive dysfunction. Translational Neurodegeneration. 2023;12(1):9. Reitz C, Tang M-X, Manly J, Schupf N, Mayeux R, Luchsinger J. Plasma lipid levels in the elderly are not associated with the risk of mild cognitive impairment. Dementia and Geriatric Cognitive Disorders. 2008;25(3):232-237. Lin Frank R, Pike James R, Albert Marilyn S, Arnold Michelle, Burgard Sheila, Chisolm Theresa... & Coresh Josef. Hearing intervention versus health education control to reduce cognitive decline in older adults with hearing loss in the USA: a multicentre, randomised controlled trial. Lancet.2023;402(10404):786-797. Gatchel JR, Donovan NJ, Locascio JJ, Schultz AP, Becker JA, Chhatwal J, Papp KV, Amariglio RE, Rentz DM, Blacker D, Sperling RA, Johnson KA, Marshall GA. Depressive symptoms and tau accumulation in the inferior temporal lobe and entorhinal cortex in cognitively normal older adults: A pilot study. Journal of Alzheimer's Disease. 2017;59(3):975-985. Coutinho G, Drummond C, Teldeschi A, Mattos P. Awareness of memory deficits is useful to distinguish between depression and mild cognitive impairment in the elderly. Brazilian Journal of Psychiatry. 2016;38(3):231-234. Hou D-c, Sun Y-m, Liu Z-k, Sun H-y, Li Y, Wang R. A longitudinal study of factors associated with cognitive frailty in elderly population based on the health ecology model. Journal of Affective Disorders. 2024;352:410-418. Song Y, Liu Y, Bai X & Yu H. Effects of neighborhood built environment on cognitive function in older adults: a systematic review. BMC Geriatrics. 2024;24(1). Mani A, Mullainathan S, Shafir E & Zhao J. Poverty impedes cognitive function. Science ,2013,341(6149):976-980. Leist AK, Novella R, Olivera J. The role of nutrition and literacy on the cognitive functioning of elderly poor individuals. Journal of Aging & Social Policy. 2020;32(3):276-295. Sharifi S, Babaei Khorzoughi K, Khaledi-Paveh B, Rahmati M. Association of intergenerational relationship and supports with cognitive performance in older adults: A systematic review. Geriatric Nursing. 2023;52:146-151. Jiang T. Mediating effects and moderating effects in causal inference. China Industrial Economics, 2022, 5: 100-120. Yi X-j, Zhang L-s, Xu S, Zhou C. Commercial Health Insurance, Precautionary Motivesand Household Consumption:Theoretical Analysis and Empirical Evidence.Journal of Financial Research, 2023, (4): 130-148. (In Chinese) Hu Y, Peng W, Ren R, Wang Y & Wang, Ge. Sarcopenia and mild cognitive impairment among elderly adults: the first longitudinal evidence from CHARLS. Journal of cachexia, sarcopenia and muscle, 2022, 13(6): 2944-2952. Flamion A, Missotten P, Marquet M & Adam, S. Impact of contact with grandparents on children's and adolescents’ views on the elderly. Child development, 2019, 90(4): 1155-1169. Yan Y, Du Y, Li X, Ping W, & Chang Y. Physical function, ADL, and depressive symptoms in Chinese elderly: Evidence from the CHARLS. Frontiers in Public Health, 2023, 11: 1017689. Li Y, Zhao D. Education, neighbourhood context and depression of elderly Chinese. Urban Studies, 2021, 58(16): 3354-3370. Luo J, Cui M. For children or grandchildren?—The motivation of intergenerational care for the elderly in China. International Journal of Environmental Research and Public Health, 2023, 20(2): 1441. Tang S, Xu Y, Li Z, Yang T & Qian D. Does economic support have an impact on the health status of elderly patients with chronic diseases in China?-based on CHARLS (2018) data research. Frontiers in Public Health, 2021, 9: 658830. Liao S, Qi L, Xiong J, Yan J & Wang R. Intergenerational ties in context: Association between caring for grandchildren and cognitive function in older Chinese. International Journal of Environmental Research and Public Health, 2021, 18(1): 21. Yin Z-c, Zhang C. The influence of married women’s labor force participation on the household saving rate. Economic Research Journal. 2019;54(4):165-181. (In Chinese). Böhme M H, Persian R, Stöhr T. Alone but better off? Adult child migration and health of elderly parents in Moldova. Journal of Health Economics, 2015, 39: 211-227. Wang Y, Zhou C. Promoting social engagement of the elderly to cope with aging of the Chinese population. BioScience Trends, 2020, 14(4): 310-313. Hu Y, Wang Z, Wu L. Multidimensional health heterogeneity of Chinese older adults and its determinants. SSM-Population Health, 2023, 24: 101547. Zhang Y, Chen G, He Y, Jiang X, Xue C. Social interaction in public spaces and well-being among elderly women: towards age-friendly urban environments. International journal of environmental research and public health, 2022, 19(2): 746. Portegijs E, Lee C, Zhu X. Activity-friendly environments for active aging: The physical, social, and technology environments. Frontiers in public health, 2023, 10: 1080148. Tian S-y. Analysis of health-related quality of life of elderly people living alone in Shanghai. Academic Journal of Second Military Medical University, 2018: 258-262. Xiang Q-q, LI S-z, Fang W-l, & Chen K-x. Relationship between psychological capital and life quality in elderly people. Chinese Mental Health Journal, 2017: 718-722. Additional Declarations No competing interests reported. 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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-4387499","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":302712387,"identity":"49dc2715-c45e-4e83-ad00-552230808683","order_by":0,"name":"Feng Chen","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Chen","suffix":""},{"id":302712388,"identity":"961884c3-157a-42d6-93ef-f0b6a01f7614","order_by":1,"name":"Ruixin Gao","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Ruixin","middleName":"","lastName":"Gao","suffix":""},{"id":302712389,"identity":"250e0182-9224-4196-98a2-9d5dfbbc12c5","order_by":2,"name":"Lihua Ma","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYFAC5obDQLKeXwLMk5AhQgsjWEuC5AwgC6iFhygtzCAtBjfAWhgIa9FtP9h4uLDNLs/4dvPxRzdqLHgY2A8f3YBPi9mZxIbDM9uSi83uHEtszjkGdBhPWtoNvFoOALXwtjEzbruRY9icwwbUIsFjhl/L+YcgLfWMm2eAtPwjRssNsC2HEzdIALXkthGlBWgLz7njxhI30hJn5/ZJ8LAR9Mv55MOfecqq5fhnJB/4nPOtTo6f/fAxvFowARtpykfBKBgFo2AUYAMAPDtMpHntfOMAAAAASUVORK5CYII=","orcid":"","institution":"East China Normal University","correspondingAuthor":true,"prefix":"","firstName":"Lihua","middleName":"","lastName":"Ma","suffix":""},{"id":302712390,"identity":"d24756dd-8cb3-450b-8ec2-7ed419d62ede","order_by":3,"name":"Linyi Qian","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Linyi","middleName":"","lastName":"Qian","suffix":""},{"id":302712391,"identity":"2a7218d1-b1cc-4b8f-b7aa-c31058f8e85b","order_by":4,"name":"Lianxing Yang","email":"","orcid":"","institution":"East China Normal University","correspondingAuthor":false,"prefix":"","firstName":"Lianxing","middleName":"","lastName":"Yang","suffix":""},{"id":302712392,"identity":"d2d272ab-499b-4fdd-9ff9-d4405c89f432","order_by":5,"name":"Zhixin Yang","email":"","orcid":"","institution":"Ball State University","correspondingAuthor":false,"prefix":"","firstName":"Zhixin","middleName":"","lastName":"Yang","suffix":""}],"badges":[],"createdAt":"2024-05-08 07:57:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4387499/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4387499/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66538936,"identity":"305300e4-ec61-4e83-8341-b97c0de01c34","added_by":"auto","created_at":"2024-10-14 07:24:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":884565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4387499/v1/54180bed-e51a-4a3f-ae28-75b463047c8c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can Skip-generation Caregiving Improve the Quality of Life for the Elderly?","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWith the rapid development of the economy and continuous changes in the population structure, the issue of aging in China has become increasingly prominent. According to the 2023 National Report on the Development of Aging Affairs, by the end of 2023. Currently, the proportion of the elderly population aged 60 and above has surpassed 20%. Around 2035, China is expected to enter the stage of severe aging. Meanwhile, China's average life expectancy has steadily increased, from 71.4 years in 2000 to 78.2 years in 2021, indicating that the physical condition of the retired elderly population remains relatively good, with potential to contribute to their families or society. In addressing the challenges of an aging demographic, the emphasis has been placed on the advancement of the 'Healthy China initiative' as a proactive approach to counteract the impacts of population aging.\u003c/p\u003e \u003cp\u003eAs life expectancy increases, so does the risk of physical and cognitive disabilities among the elderly [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], raising concerns about their quality of life. The cognitive abilities of the elderly significantly affect their quality of life. The \"Alzheimer's Patient Needs Insight Report\" released in 2023 points out that Alzheimer's patients in China are mainly elderly but show a trend towards younger ages. The \"Healthy China Action\" plan aims to reduce the incidence of dementia among individuals aged 65 and above by 2030, Achieving this objective necessitates the continuous identification and implementation of effective strategies to prevent cognitive deterioration. The principle of \u0026lsquo;use it or lose it\u0026rsquo; suggests maintaining good cognition requires elderly people to remain mentally active and socially connected after retirement. Traditionally, Chinese extended families have tight-knit relationships, with members mutually providing caregiving and support. The skip-generation caregiving model, where elderly family members care for their grandchildren, is a common practice that leverages the labor resources of the elderly to facilitate their participation in social activities, potentially slowing cognitive decline and improving their life quality in old age.\u003c/p\u003e \u003cp\u003eData from the China Health and Retirement Longitudinal Study (CHARLS) show that 37.87% of families in China engage in skip-generation caregiving, with grandparents and their partners spending an average of 44.61 hours per week to childcare. This model not only mitigates the risk of the elderly experiencing an empty nest syndrome but also benefits their physical, mental, and cognitive health [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite its advantages, skip-generation caregiving can significantly alter the social relationships of the elderly, introducing challenges. The \"China Migration Development Report 2016\" shows that nearly 18\u0026nbsp;million of China's aging migrant population, 43% of whom relocate to provide childcare, struggle to adapt to new environments, potentially leading to cognitive decline. Hence, the actual impact of skip-generation caregiving on the cognitive status of the elderly remains unclear.\u003c/p\u003e \u003cp\u003eThis paper seeks to empirically explore the effect of skip-generation caregiving on the cognitive abilities of the elderly. It distinguishes itself from previous studies in several key ways: First, it employs scientific indicators to measure cognitive abilities, relying on the accuracy of responses to specific questions instead of self-assessment, thus ensuring greater rigor in the study. Secondly, it acknowledges that skip-generation caregiving profoundly impacts the social environment, mental state, and economic resources of the elderly. These three aspects are integrated as mediating variables in the model, thereby enriching the practical relevance of the findings. Thirdly, in alignment with the objectives of the \u0026lsquo;Healthy China initiative\u0026rsquo; and its proactive approach to aging, this paper verifies the impact of skip-generation caregiving behavior on the quality of life of the elderly based on the China Health and Retirement Longitudinal Study, providing a more scientific analysis of the impact mechanisms. Additionally, it conducts a heterogeneity analysis based on age and economic status and performs robustness tests on the results, making the conclusions more accurate and deepening the understanding of the mechanisms by which skip-generation caregiving affects the cognitive abilities of the elderly. This work represents an insightful case study from a developing country, significantly enriching the global discourse on intergenerational caregiving dynamics.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eDue to tight intergenerational bonds and limited childcare facilities, caregiving by grandparents has become a prevalent practice in China. A significant number of scholars have explored the effects of this caregiving model on elderly lives, focusing their research on its impact on grandparents' living conditions, mental health, and self-awareness of their needs. Yet, the academic community has not reached a consensus regarding the impact of such caregiving on the cognitive abilities of older adults. Caring for grandchildren significantly transforms the lives of elderly individuals by increasing their physical activity and strengthening bonds with their children, leading to a more engaging lifestyle. Studies by Bonsang et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] and Atalay et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] indicate that retirement can negatively impact the cognitive functions of older adults. However, engaging in grandparenting activities can enhance their participation in the labor force and slow cognitive decline. Arpino and Bordone [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] posited that caregiving activities by grandparents can escalate intellectual engagement, hence preserving their analytical and memory skills and preventing cognitive deterioration. This research also found that grandparents who engage in caregiving activities demonstrate notable improvements in linguistic fluency. In China, many \"floating elders\" who move to live with their children in their later years receive significant emotional support from their families. Engaging in grandparenting markedly increases interactions between older adults and their children [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], enhancing grandparents' sense of well-being and supporting cognitive health. However, although the studies acknowledge positive effects, they often oversimplify the mechanisms through which grandparenting influences cognitive abilities. Commonly, they suggest that caregiving offers additional mental stimulation, thereby helping to prevent cognitive decline. Although this effect is evident, it does not encompass all contributing factors.\u003c/p\u003e \u003cp\u003eFurthermore, grandchild care can lead to psychological stress and depression in grandparents, with these adverse emotions varying based on social contexts. In places like the United States [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and Kenya [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], caregiving is seen as a major stressor for grandparents, potentially leading to depression, anxiety, and cognitive impairments. Ates [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], analyzing data from the German Ageing Survey (DEAS), discovered that caregiving has a modestly positive impact on the physical and psychological health of German elders. In China, caregiving often positively affects older adults' mental health. Research by Xu [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and Choi and Zhang [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] suggests that grandparenting can sustain positive mental health in Chinese elders, also reducing the likelihood of chronic conditions like hypertension. Age is also one of the primary factors affecting the physical and mental health of elderly individuals in real life. Existing research on the role of age in the process of grandparenting is somewhat cursory, lacking a detailed investigation into how age variations affect this dynamic. This article aims to conduct a heterogeneity analysis based on age, thereby filling this gap in the literature.\u003c/p\u003e \u003cp\u003eSome studies have pointed out that caregiving impacts the promptness of medical care among the elderly, yet effect of this influence remains contentious. Research by Baker and Silverstein [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]showed that grandmothers who provide care are more diligent about undergoing health screenings and vaccinations. Di Gessa et al. [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], through their analysis of European elder retirement data, noted that grandparenting enhances the financial and temporal support from children, encouraging elders to monitor their health closely. Wang et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] argued that extended caregiving might lead to a neglect of the grandparents' own health needs. This variance in findings could stem from different levels of caregiving intensity; a lower intensity may foster intimate relationships and health vigilance, whereas a higher intensity of caregiving could overshadow the grandparents' health issues. This paper will specifically examine the effects of caregiving intensity on these dynamics.\u003c/p\u003e"},{"header":"3. Theoretical Analysis and Research Hypotheses","content":"\u003cp\u003eThe cognitive decline faced by elderly individuals can significantly impact their physical and mental health, as well as their ability to live independently. To decelerate this decline, scholars globally have investigated the factors that influence cognitive functions. Present discussions have identified five primary factors affecting the cognitive abilities of the elderly: the factors influencing the cognitive abilities of the elderly can primarily be summarized into five aspects: personal lifestyle, physical and mental health, degree of social participation, and intergenerational economic support.\u003c/p\u003e \u003cp\u003ePersonal lifestyle choices, such as smoking, alcohol consumption, and engagement in leisure activities, have a direct impact on cognitive functions. Liu et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] analyzed the cognitive decline trajectory of elderly individuals, finding that moderate sleep, regular exercise, and dietary habits could significantly mitigate cognitive deterioration. Both mitigate cognitive deterioration have a negative impact on cognitive abilities. Lu et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] explored the factors contributing to dementia in older adults, discovering that consistent physical exercise and work protect brain and reduce dementia risk.\u003c/p\u003e \u003cp\u003eThe physical and mental health of elderly individuals impact their cognitive abilities through different mechanisms. Reitz et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] argued that the coexistence of hypertension and hyperlipidemia indirectly leads to neuronal function impairment, thus cognitive decline. Moreover, improved hearing can decelerate cognitive decline [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Negative emotions including depression and anxiety negatively impact cognitive functions and indirectly lower cognitive abilities through influencing individual behavior. Gatchel et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] suggested that depressed elderly individuals are more likely to develop dementia, with depression potentially being a precursor to dementia. Coutinho et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found that severe depression accelerates memory decline in the elderly, severely negatively affecting their cognitive functions.\u003c/p\u003e \u003cp\u003eA higher degree of social engagement encourages the acquisition of new knowledge among elderly individuals, thereby protecting their cognitive abilities. Hou et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] found that elderly individuals active in social activities have better memory, making social participation a protective factor for cognitive abilities. Song et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] studied the living environments of elderly Americans, finding those residing in densely populated communities exhibit higher cognitive abilities, likely due to varied degrees of social engagement in different community settings.\u003c/p\u003e \u003cp\u003eEconomic support from adult children improves the living conditions of the elderly, thus influencing their cognitive functions. Mani et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] found that the economic status of elderly individuals significantly impacts their cognitive abilities in later life, with economically disadvantaged elderly individuals often also having poor nutrition and lower education levels. Moreover, concerns about economic conditions can hinder individual cognitive function [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Sharifi et al. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] investigated the potential link between intergenerational relations and cognitive performance among elderly individuals in East Asian countries, finding that frequent intergenerational economic exchanges help maintain cognitive health among the elderly.\u003c/p\u003e \u003cp\u003eBased on the above analysis, this article proposes the following hypotheses:\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 1\u003c/strong\u003e \u003cp\u003eThrough caregiving for grandchildren, grandparents may experience enhanced self-worth, thereby obtaining self-identity and reducing loneliness after retirement. Grandparenting indirectly bolsters their cognitive abilities by alleviating depression.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 2\u003c/strong\u003e \u003cp\u003eGrandparenting after retirement strengthens social ties for the elderly, encouraging them to participate more in social activities and increase daily exercise. Grandparenting has a positive impact on their cognitive abilities by enriching the complexity of their social networks.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHypothesis 3\u003c/strong\u003e \u003cp\u003eFamilies engaged in grandparenting have closer intergenerational ties and higher levels of intergenerational economic support, providing elderly individuals with better health monitoring and medical environments, positively affecting their cognitive abilities.\u003c/p\u003e \u003c/p\u003e"},{"header":"4. Research Design and Data Description","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Model Setup\u003c/h2\u003e \u003cp\u003e \u003cem\u003eBaseline Regression\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThis paper employs a two-way fixed effect, establishing the econometric model as follows:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${Y}_{i}={\\alpha }_{0}+{\\alpha }_{1}{C}_{i}+{\\alpha }_{2}{X}_{i}+{\\delta }_{c}+{\\delta }_{t}+{\\epsilon }_{i}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe dependent variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Y}_{i}\\)\u003c/span\u003e\u003c/span\u003e represents the cognitive abilities of the elderly population. The core explanatory variables \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({C}_{i}\\)\u003c/span\u003e\u003c/span\u003e, include \"whether to perform skip-generation caregiving\" and \"the intensity of skip-generation caregiving\". Control variables \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({X}_{i}\\)\u003c/span\u003e\u003c/span\u003e are incorporated, and the parameter of interest \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\alpha }_{1}\\)\u003c/span\u003e\u003c/span\u003e represents the impact of explanatory variables on the dependent variable. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\delta }_{c}\\)\u003c/span\u003e\u003c/span\u003e represents unchanging regional fixed effects, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\delta }_{t}\\)\u003c/span\u003e\u003c/span\u003e represents survey year fixed effects, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\epsilon }_{i}\\)\u003c/span\u003e\u003c/span\u003e is the random error term.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMechanism Analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe mechanism analysis follows the approach of Jiang [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] and Yi et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], utilizing mechanism variables that have a proven causal relationship and are temporally and logically close as mediating variables, rather than formal causal inference steps. This paper conducts regression analyses of psychological health status, social relationship complexity, and intergenerational economic support on the presence of skip-generation caregiving to investigate the mechanisms involved.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$${M}_{i}={\\beta }_{0}+{\\beta }_{1}{C}_{i}+{{\\beta }_{2}X}_{i}+{\\delta }_{c}+{\\delta }_{t}+{\\epsilon }_{i}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe mechanism variable \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({M}_{i}\\)\u003c/span\u003e\u003c/span\u003e includes psychological health status, social relationship complexity, and intergenerational economic support as model mechanism variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Data Source and Processing\u003c/h2\u003e \u003cp\u003eThe data for this study are sourced from the China Health and Retirement Longitudinal Study (CHARLS), which focuses on Chinese individuals aged 45 and above. The survey encompasses 28 provinces, 150 county units, 450 village units, and roughly 17,000 individuals across 10,000 households. The data contain personal basic information, physical health status, cognitive and depression conditions, income, and property, etc., closely aligning with the research objectives of this study. This comprehensive database was selected to provide robust data support for our analysis. For this paper, mixed cross-sectional data from the years 2012, 2015, and 2018 were utilized. Samples lacking children or grandchildren and individuals older than 85 years were excluded, yielding 9,814 valid observations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Variable Selection and Description\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 Dependent Variable: Cognitive Ability of Elderly People\u003c/h2\u003e \u003cp\u003eCognitive abilities are assessed using specific test scales, with scores assigned accordingly. The test, conducted via questionnaire, evaluates various cognitive domains including temporal orientation, attention and calculation, spatial abilities, language proficiency, and both immediate and delayed memory functions [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. For categorical questions, each correct answer is awarded 1 point. For quantitative questions, points are awarded based on the number of correct responses, while refusals or failures to answer are scored as 0. The maximum possible score for the cognitive ability test section is 80 points. The full score for the cognitive ability test part is 80 points, with higher scores indicating higher levels of cognitive ability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Core Explanatory Variables: Whether to Perform skip-generation caregiving and the Intensity of skip-generation caregiving\u003c/h2\u003e \u003cp\u003e\"Whether to perform skip-generation caregiving\" and \"the intensity of skip-generation caregiving\" are selected as core explanatory variables. The survey inquires of respondents with grandchildren under the age of 16 whether they or their spouse have spent time in the past year caring for their grandchildren, with the possible responses being \"yes\" or \"no\". If skip-generation caregiving behavior exists, the value is 1; otherwise, it's 0. The intensity of skip-generation caregiving is measured by two dimensions: the number of grandchildren cared for and the weekly hours spent on skip-generation caregiving. According to the method applied by Flamion [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], in cases where elderly family members do not reside with their grandchildren but still engage in skip-generation caregiving, the average time spent on such caregiving is calculated. The variables thus capture the actual number of grandchildren under 16 cared for and the weekly hours dedicated to skip-generation caregiving.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e4.3.3 Mechanism Variables: Psychological Health Status, Social Relationship Complexity, and Intergenerational Economic Support\u003c/h2\u003e \u003cp\u003eFirstly, the degree of depression is selected as a measure of the psychological health status of elderly people. CHARLS survey utilizes the CESD-10 scale to measure symptoms of depression[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], consisting of 10 items each rated between 0\u0026ndash;3 according to the frequency of the symptoms experienced. A higher total score indicates more severe depressive symptoms, with scores of 10 or above classified as indicative of depressive symptoms[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Scores\u0026thinsp;\u0026ge;\u0026thinsp;10 are defined as having depressive symptoms, with an overall Cronbach's α coefficient of 0.802.Secondly, in line with prior research, the complexity of social relationships and intergenerational economic support are identified as mechanism variables that influence cognitive ability, reflecting how these factors potentially affect cognitive functions in the elderly.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e4.3.4 Control Variables\u003c/h2\u003e \u003cp\u003eTo address the issue of endogeneity arising from omitted variables, the model incorporates a comprehensive set of control variables. These variables are categorized across individual, family, and city/regional levels to ensure a thorough analysis.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAt the individual level, control variables include\u003c/strong\u003e \u003cp\u003eAge, square of age, gender, marital status, education level, self-rated health status, intensity of daily exercise, degree of chronic illness, sleep duration, lifestyle habits, personal pension.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAt the family level, variables encompass\u003c/strong\u003e \u003cp\u003eTotal income, net assets, household size, household consumption expenditure, child dependency ratio, elderly dependency ratio, homeownership, debt ownership, and whether the household is in a rural area.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAdditional city and regional level control variables include\u003c/strong\u003e \u003cp\u003eThe per capita GDP of the region, local fiscal budget, local fiscal spending on science and education, the share of secondary industry in GDP, the share of tertiary industry in GDP, and categorical variables for eastern, western, and central regions.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"5. Empirical Analysis","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Baseline Regression\u003c/h2\u003e \u003cp\u003e \u003cem\u003eBaseline Analysis: The Impact of skip-generation caregiving on the Cognitive Abilities of Elderly People\u003c/em\u003e \u003c/p\u003e \u003cp\u003eIn the baseline regression, cognitive ability is used as the dependent variable, with the presence of skip-generation caregiving as the core explanatory variable. Personal characteristic control variables and family characteristic control variables are progressively introduced into the regression for estimation.\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\u003eRegression Results for the Impact of Grandparenting on Cognitive Ability\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOLS (2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOLS (3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6518***\u003c/p\u003e \u003cp\u003e(0.1565)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6981***\u003c/p\u003e \u003cp\u003e(0.1598)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5601***\u003c/p\u003e \u003cp\u003e(0.1551)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual and Household-level Control Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional-level Control Variables\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\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9814\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\u003eAccording to the regression results shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, with the continuous introduction of control variables, skip-generation caregiving has a positive impact on the cognitive abilities of elderly people and is significant at the 1% level of significance. This is consistent with the conclusions drawn in the theoretical summary of this paper. Specifically, skip-generation caregiving leads to an increase of 0.5601 in the scale score, which is about a 15% improvement. This enhancement likely stems from the direct increase in daily physical activity among elderly individuals due to skip-generation caregiving behavior, the improvement in their level of social participation, and indirectly increasing their sense of self-identity. Such factors collectively foster the physical and mental health of elderly individuals, thereby supporting the maintenance of robust cognitive functions.\u003c/p\u003e \u003cp\u003eBaseline Analysis: The Impact of skip-generation caregiving Intensity on the Cognitive Abilities of Elderly People\u003c/p\u003e \u003cp\u003eIn light of the variations in skip-generation caregiving levels among individuals, this study has refined its approach by substituting the dependent variable with three new measures: the number of grandchildren cared for, the weekly hours spent on skip-generation caregiving, and skip-generation caregiving intensity. Here, skip-generation caregiving intensity is defined as the product of the time spent caregiving and the number of grandchildren cared for. This adjustment is made while retaining the core explanatory variables and control variables as constant.\u003c/p\u003e \u003cp\u003eThe impact of skip-generation caregiving intensity on the cognitive abilities of elderly individuals and the intrinsic connection of this impact might be that as the intensity of skip-generation caregiving increases, the connection between elderly individuals and their families becomes closer[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This helps reduce depression caused by loneliness and gain more economic support from children[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, a higher intensity of skip-generation caregiving enhances the interaction between grandparents and society at large. It enriches the complexity of their social relationships, which, in turn, contributes to a reduced risk of cognitive decline. The subsequent sections of this text will delve deeper into the mechanisms by which skip-generation caregiving influences cognitive abilities\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 for the Impact of Grandparenting Intensity on Cognitive Ability\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOLS (2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOLS (3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Grandchildren Cared For\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.15*** \u003c/p\u003e \u003cp\u003e(0.03416)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly Grandparenting Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.05588 ***\u003c/p\u003e \u003cp\u003e(0.01183)\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\u003eGrandparenting Intensity\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\u003e0.02253***\u003c/p\u003e \u003cp\u003e(0.004852)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual, Time Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9814\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\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e the number of grandchildren cared for, the weekly skip-generation caregiving time, and the skip-generation caregiving intensity have a positive effect on the cognitive function of elderly people, and this positive effect is significant at the 1% level of significance.\u003c/p\u003e \u003cp\u003eThese results indicate a positive correlation between skip-generation caregiving and the cognitive abilities of elderly people, with an increase in the number of grandchildren cared for and the increase in weekly skip-generation caregiving time strengthening this positive correlation. The intrinsic connection of this impact might be that as the intensity of skip-generation caregiving increases[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], the connection between elderly people and their families also becomes closer. This helps reduce depression caused by loneliness and gain more economic support from children. Furthermore, a stronger intensity of skip-generation caregiving promotes contact between grandparents and society, increases the complexity of social relationships, thereby reducing the likelihood of cognitive decline. The following text will further explore the mechanisms through which skip-generation caregiving affects cognitive abilities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Endogeneity Problem\u003c/h2\u003e \u003cp\u003eThe decline in cognitive abilities among the elderly is influenced not only by personal factors but also by unpredictable external factors, which have a significant impact on individual cognitive capabilities, making it difficult for the model to cover all relevant explanatory variables. There is also an interplay between skip-generation caregiving behavior and cognitive abilities among the elderly. On one hand, engaging in the care of grandchildren allows elderly individuals to learn new skills, potentially delaying cognitive decline. On the other hand, when signs of cognitive impairment become apparent in grandparents, adult children might hesitate to entrust them with the care of grandchildren, decreasing the instances of skip-generation caregiving. This suggests a bidirectional causal relationship, which, along with omitted variables, introduces endogeneity issues into the study. To address this, the use of instrumental variables becomes necessary. Given the complexity surrounding the measurement of cognitive abilities and the various factors influencing them, the selection of appropriate instrumental variables is critical. Some scholars have used the gender of children, the type of children's employment, the presence of grandchildren, and the average caregiving rate in the community as potential instrumental variables for skip-generation caregiving. Following the approach used by Yin and Zhang [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], this study selects average skip-generation caregiving rate of other respondents in the same city area as the instrumental variable for engaging in skip-generation caregiving: first, the elderly population in the same city has common preferences for skip-generation caregiving behavior and are easily influenced by other elderly people in their regional environment. If the average level of skip-generation caregiving among the elderly population in the same area is higher, then the likelihood of the respondent engaging in skip-generation caregiving increases, thus satisfying the relevance condition of the instrumental variable; second, by excluding the information on whether the respondent themselves is engaged in skip-generation caregiving, the average skip-generation caregiving rate of other elderly people in the same area does not directly affect cognitive ability, avoiding correlation with the error term and satisfying the exogeneity condition of the instrumental variable; third, this method of constructing instrumental variables has been widely used in many literatures and has achieved good estimation effects.\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\u003eAddressing Endogeneity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2SLS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2SLS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e2SLS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e436.07***\u003c/p\u003e \u003cp\u003e(93.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Grandchildren Cared For\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\u003e374.66***\u003c/p\u003e \u003cp\u003e(99.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly Grandparenting Time\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.156***\u003c/p\u003e \u003cp\u003e(2.279)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstrumental Variable (IV) Status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFirst-stage F-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9814\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\u003eThe estimation results presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e illustrate that in the first stage of the two-stage least squares (2SLS) regression, as shown in columns (1), (3), and (5), the impact of the instrumental variable on the likelihood of engaging in skip-generation caregiving is significant, positive, and associated with a large F-value. This finding aligns with the prior analysis and indicates that the study does not suffer from the issue of a weak instrumental variable, which can undermine the reliability of 2SLS estimates.\u003c/p\u003e \u003cp\u003eWhen comparing the Ordinary Least Squares (OLS), ordered probit, and 2SLS estimation methods, the coefficient values derived from the second stage of the 2SLS are notably larger than those obtained through the first two methods. However, the sign direction and the fundamental conclusions drawn from these coefficients remain consistent across all methods. This suggests that while the 2SLS method yields stronger associations between skip-generation caregiving and cognitive abilities of the elderly, it fundamentally supports the same underlying relationship as identified by the simpler OLS and ordered probit analyses. This reinforces the validity of the findings regarding the positive impact of skip-generation caregiving on the cognitive functions of elderly individuals, while also highlighting the importance of addressing potential endogeneity through the use of instrumental variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Heterogeneity Analysis\u003c/h2\u003e \u003cp\u003eThe discussion thus far has largely concluded that skip-generation caregiving positively impacts cognitive abilities. In practical terms, age and economic status significantly influence the cognitive functions of elderly individuals. It is widely acknowledged that, within a certain range, cognitive abilities tend to decline with age; Conversely, elderly individuals with higher economic levels have access to better medical conditions, reducing the risk of cognitive decline. To determine whether the effect of skip-generation caregiving on cognitive abilities differs across various backgrounds, the subsequent sections will undertake a heterogeneity analysis, examining the influence from the perspectives of economic level and age. This analysis aims to uncover nuanced insights into how different factors may modulate the relationship between skip-generation caregiving and cognitive health, providing a more comprehensive understanding of the potential benefits and limitations of caregiving across diverse segments of the elderly population.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e5.3.1 Economic Level\u003c/h2\u003e \u003cp\u003eTo assess the influence of economic status on the behavior of skip-generation caregiving among the elderly, this study integrates interaction terms between the baseline regression's three core explanatory variables\u0026mdash;engagement in skip-generation caregiving, intensity of caregiving, and the number of grandchildren cared for\u0026mdash;and economic indicators such as pension income and financial support from children. As shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, the estimated coefficients of the interaction terms between the three skip-generation caregiving variables and pension are significantly positive. This implies that as pension income increases, the beneficial impact of skip-generation caregiving on the cognitive abilities of elderly individuals also grows. Meanwhile, economic support from children to their elderly parents appears to have a positive influence, though this effect does not reach statistical significance.\u003c/p\u003e \u003cp\u003eThese results indicate that elderly individuals with higher economic status, compared to their lower economic status counterparts, are more capable of leveraging skip-generation caregiving to sustain or even enhance their cognitive functions. This distinction underscores the interplay between economic resources and caregiving activities, suggesting that financial well-being can amplify the cognitive benefits associated with caregiving. The findings highlight the need for supportive policies and interventions that consider the economic backgrounds of elderly caregivers, aiming to maximize the cognitive and overall health benefits of skip-generation caregiving across different economic strata.\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\u003eEconomic Level Heterogeneity Analysis\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOLS (2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOLS (3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.099***\u003c/p\u003e \u003cp\u003e(0.2633)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting * Pension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001271***\u003c/p\u003e \u003cp\u003e(0.0002003)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting * Intergenerational Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.000007642\u003c/p\u003e \u003cp\u003e(0.00001817)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Care Recipients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6825***\u003c/p\u003e \u003cp\u003e(0.1843)\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\u003eNumber of Care Recipients * Pension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0008733***\u003c/p\u003e \u003cp\u003e(0.00015)\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\u003eNumber of Care Recipients * Intergenerational Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00006312\u003c/p\u003e \u003cp\u003e(0.0001115)\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\u003eCaregiving Time\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\u003e0.01603*\u003c/p\u003e \u003cp\u003e(0.005014)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiving Time * Pension\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\u003e0.0002686***\u003c/p\u003e \u003cp\u003e(0.00004112)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiving Time * Intergenerational Support\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\u003e0.0000005386\u003c/p\u003e \u003cp\u003e(0.00002979)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Control Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual, Regional, Time Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9814\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=\"Sec17\" class=\"Section3\"\u003e \u003ch2\u003e5.3.2 Age\u003c/h2\u003e \u003cp\u003eTo address the issue of heteroscedasticity, which often affects the reliability of regression results in cross-sectional data, this paper employs Weighted Least Squares (WLS) regression for the analysis of interaction terms between age and the core explanatory variables related to skip-generation caregiving. The regression results, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, indicate that skip-generation caregiving has a significant positive impact on cognitive levels. However, it also shows that cognitive abilities generally decrease as individuals age. The interaction terms between age and the skip-generation caregiving variables yield a negative coefficient, indicating that the beneficial impact of skip-generation caregiving on cognitive levels diminishes with advancing age.\u003c/p\u003e \u003cp\u003eThese findings suggest that while skip-generation caregiving can act as a buffer against the cognitive decline associated with aging, its effectiveness in counteracting this decline lessens as individuals grow older. This could imply that the cognitive benefits derived from caregiving activities, such as increased social interaction, mental engagement, and physical activity, have a less pronounced impact on older elderly individuals. Consequently, while skip-generation caregiving can provide a meaningful avenue for supporting cognitive health, its potential to mitigate the effects of aging on cognition is not uniform across all age groups, highlighting the need for tailored approaches in caregiving practices and policy formulations to maximize cognitive health benefits for the elderly population at different stages of aging.\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\u003eAge Heterogeneity Analysis\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWLS (2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWLS (3)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-76.06***\u003c/p\u003e \u003cp\u003e(1.364)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-76.31***\u003c/p\u003e \u003cp\u003e(1.283)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-82.21***\u003c/p\u003e \u003cp\u003e(1.243)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.05***\u003c/p\u003e \u003cp\u003e(3.238)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting * Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-16.86***\u003c/p\u003e \u003cp\u003e(0.8121)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Care Recipients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.22***\u003c/p\u003e \u003cp\u003e(2.394)\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\u003eNumber of Care Recipients * Age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-14.74***\u003c/p\u003e \u003cp\u003e(0.6043)\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\u003eCaregiving Time\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\u003e1.571***\u003c/p\u003e \u003cp\u003e(0.005514)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaregiving Time * Age\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-40.16***\u003c/p\u003e \u003cp\u003e(0.001396)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Control Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual, Regional, Time Fixed Effects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9814\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 \u003c/div\u003e"},{"header":"6. Robustness Tests","content":"\u003cp\u003eTo ensure the rigor of the research conclusions, this paper conducts robustness tests by replacing the dependent variable from two aspects. Firstly, self-rated memory scores are used instead of cognitive abilities to test the robustness of the regression results. In the valuation of the self-rated memory score variable, this study assigns values sequentially as 5 (excellent), 4 (very good), 3 (good), 2 (fair), 1 (poor), and 0 (very poor) for research. Considering potential minor differences in individual assessments, these ratings are presumed to follow a Poisson distribution to accentuate variability. Secondly, considering that changes in cognitive abilities occur over an extended period, the explanatory power of skip-generation caregiving in the past year on the strength of cognitive abilities is somewhat limited. This paper uses \"change in cognitive ability\" as the dependent variable for robustness testing. This metric assesses any decline in cognitive scores of the participants relative to their previous evaluation (either in 2015 or 2012), with a decrease denoted by 0 and stability or improvement by 1.\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\u003eRobustness Tests\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eRobustness Test 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRobustness Test 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eSelf-Rated Memory Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eChange in Cognitive Ability\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03571*\u003c/p\u003e \u003cp\u003e(0.0166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0906** \u003c/p\u003e \u003cp\u003e(0.0282)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeekly Grandparenting Time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.0413*** \u003c/p\u003e \u003cp\u003e(0.0111)\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\u003eControl Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9684\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\u003eThe data in columns (2) to (4) of Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e reveal that both engaging in skip-generation caregiving and the duration of caregiving are positively correlated with self-rated memory scores, exhibiting notable significance. Furthermore, skip-generation caregiving is shown to decrease the likelihood of a decline in cognitive abilities over time.\u003c/p\u003e \u003cp\u003eThese research results indicate that the conclusions of this paper are fundamentally robust.\u003c/p\u003e"},{"header":"7. Mechanism Analysis","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e7.1 Impact Mechanism: Psychological Health Status\u003c/h2\u003e \u003cp\u003eThe regression results displayed in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e show that skip-generation caregiving significantly reduces depression levels and markedly improves psychological health. This suggests that skip-generation caregiving indirectly boosts cognitive abilities by enhancing psychological health, aligning with Hypothesis (1) of this study.\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\u003eImpact Mechanism of Psychological Health Status\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\u003eOLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrdered Tobit (2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOLS (3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOrdered Tobit (4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(Depression Level)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(Depression Level)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(Self-rated Psychological Health)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(Self-rated Psychological Health)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.4839***\u003c/p\u003e \u003cp\u003e(0.1889)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.4771*\u003c/p\u003e \u003cp\u003e(0.1897)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.4239***\u003c/p\u003e \u003cp\u003e(0.1017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4126***\u003c/p\u003e \u003cp\u003e(0.0921)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9814\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=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e7.2 Impact Mechanism: Complexity of Social Relationships\u003c/h2\u003e \u003cp\u003eThe findings presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e indicate that participation in skip-generation caregiving significantly enhances the complexity of social relationships. This underscores the role of skip-generation caregiving in fostering social connections, thereby substantiating our theoretical hypothesis (2). According to this hypothesis, the behavior associated with skip-generation caregiving exerts a positive influence on cognitive abilities among the elderly by enriching the complexity of their social interactions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImpact Mechanism of Complexity of Social Relationships\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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrdered Tobit (2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplexity of Social Relationships\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComplexity of Social Relationships\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1366*\u003c/p\u003e \u003cp\u003e(0.05862)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1363*\u003c/p\u003e \u003cp\u003e(0.05861)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\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=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e7.3 Impact Mechanism: Intergenerational Economic Support\u003c/h2\u003e \u003cp\u003eIn this section, our approach to collecting data on economic factors mirrors that of B\u0026ouml;hme et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. We consider the economic support provided by children as a mechanism variable, taking into account the direct or indirect household expenses that may increase due to skip-generation caregiving. For instance, as illustrated in the first column of Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e, engaging in skip-generation caregiving leads to an increase in household consumption. However, this increase in expenses is relatively minor, and the overall economic comfort level of the household improves. This supports Hypothesis (3), suggesting that indirectly improving cognitive levels through improving a better health monitoring and medical environment positively affects the cognitive abilities of elderly people.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImpact Mechanism of Intergenerational Economic 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\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLS (1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOrdered Tobit (2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntergenerational Economic Support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntergenerational Economic Support\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrandparenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1259***\u003c/p\u003e \u003cp\u003e(250.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2535*** \u003c/p\u003e \u003cp\u003e(328.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl Variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9814\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"},{"header":"8. Research significance and limitations","content":"\u003cp\u003eTo comprehensively examine the influence of intergenerational grandparenting on the quality of life among the elderly, it is imperative to access long-term data capturing their engagement in such activities, the extent of involvement, and various facets of their living conditions. This paper opts for the China Health and Retirement Longitudinal Study (CHARLS) and utilizes cognitive function among the elderly as a metric for assessing their quality of life. Intergenerational grandparenting intensity is gauged by both the duration of weekly involvement and the number of grandchildren cared for. Noteworthy is our dataset's inclusion of physical and mental health indices, as well as social standing, enabling us to delve into the underlying mechanisms through which intergenerational grandparenting influences their quality of life, thus providing distinct insights from developing nations.\u003c/p\u003e \u003cp\u003eOur findings indicate a significant enhancement in the cognitive function of Chinese elderly through intergenerational childcare practices. Elderly individuals engaged in such care experienced a notable improvement in cognitive function scores, approximately a 15% increase equating to 0.5601. Moreover, within a certain range, an increase in either the number of grandchildren cared for or the weekly time dedicated to intergenerational childcare significantly bolstered elderly cognitive function. These outcomes may stem from heightened physical activity resulting from childcare responsibilities or from strengthened family bonds and social connections fostering improved mental well-being among the elderly.\u003c/p\u003e \u003cp\u003eThrough heterogeneity analysis, we observed that younger age and higher economic status among the elderly were associated with better mitigation of cognitive decline through grandparenting. Mechanism analysis revealed indirect enhancements in cognitive function among the elderly through reduced depression levels, augmented complexity in social relations, and reinforced intergenerational economic support facilitated by grandparenting. Ultimately, our study underscores the multifaceted impact of grandparenting on the cognitive function of Chinese elderly, ultimately enhancing their quality of life.\u003c/p\u003e \u003cp\u003eThe implications of our study are significant, offering avenues for retired elderly individuals to sustain their quality of life, aligning with strategies aimed at addressing aging populations [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Additionally, it suggests leveraging the elderly's contribution to family care, thus alleviating parental pressures and childbirth burdens. For instance, policies encouraging intergenerational childcare participation could lead to a 15% average improvement in cognitive function among elderly individuals, consequently enhancing their overall quality of life.\u003c/p\u003e \u003cp\u003ePolicy interventions could focus on promoting grandparenting as a means to enhance elderly quality of life, emphasizing its benefits for both the elderly and their families. Establishing an elderly-friendly social environment [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], reducing barriers to grandparenting, and facilitating their integration into society are potential strategies. However, the effectiveness of such measures in promoting grandparenting warrants further investigation beyond the scope of this study, highlighting an avenue for future research.\u003c/p\u003e \u003cp\u003eFor future research directions, this work relies on cognitive ability as a proxy for elderly quality of life. Future studies could enrich our understanding of elderly quality of life by broadening the scope of assessment beyond cognitive ability. Incorporating measures of economic status, physical health, and emotional well-being would provide a more comprehensive understanding of the factors influencing elderly well-being.\u003c/p\u003e \u003cp\u003eFor limitations, this work primarily relies on cognitive ability to gauge the quality of life among elderly individuals. While cognitive ability undoubtedly plays a significant role, it's also important to acknowledge that factors like economic status, physical health, and overall happiness are equally pivotal in evaluating the quality of life in this demographic [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFurthermore, the discussion on the influencing mechanism of intergenerational care in this study predominantly focuses on three pathways: mental health, social relations, and intergenerational support. However, the potential impact of intergenerational care on elderly individuals encompasses a broader spectrum. For instance, it can contribute to regularizing the daily routines and activities of the elderly, thereby potentially maintaining cognitive abilities. Recognizing the challenges associated with quantitatively studying additional pathways, this study opts to concentrate on these three influential factors. Additionally, the research methodology employed in the mechanism section begins with identifying correlations between the selected mechanism variables and the cognitive abilities of elderly individuals through literature research and is followed by an exploration of the direct effects of intergenerational caregiving on these variables. At the same time, it's important to acknowledge that such impacts may be more intricate, influenced by numerous exogenous factors.\u003c/p\u003e \u003cp\u003eMoreover, this study utilizes mixed cross-sectional data, thus does not aim to capture the longitudinal impact of grandparents' caregiving on individuals throughout the aging process. Due to adjustments in the questionnaire questions in 2012, 2015, and 2018, the cognitive ability scores of the same individual are not directly comparable across different years, precluding the utilization of panel data in this analysis. However, it's worth noting that in real-life scenarios, elderly individuals may commence providing intergenerational care as they age, potentially leading to instances where cognitive decline is halted or even reversed\u0026mdash;a topic that remains pertinent and warrants further discussion.\u003c/p\u003e"},{"header":"9. Conclusion","content":"\u003cp\u003e1.Historical data show that the Chinese elderly who are raising grandchildren have a significantly higher quality of life, and the increase in the intensity of parenting is conducive to the improvement of the quality of life of the elderly.\u003c/p\u003e \u003cp\u003e2.The higher the economic level of the elderly, the lower the age, and the greater benefits skip-generation caregiving will bring.\u003c/p\u003e \u003cp\u003e3.Encouraging the elderly to carry out skip-generation caregiving may reduce the burden of childbirth on young parents and improve the quality of life of the elderly, which is one of the feasible measures to actively cope with the aging of the population.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThank you to all the aged people who participated in the experiment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: FC, RG, LM. Data analysis: FC, RG, LQ. Funding acquisition: LM, FC, LQ. Methodology: LY, RG, ZY. Writing original draft: RG, FC, LQ. Writing review \u0026amp; editing: ZY, LM, LY. All authors assisted with writing the article and have approved the citation of their names in the paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (12171158), the National Social Science Foundation of China\u0026apos;s general project on education (BJA220248), the State Key Program of National Natural Science Foundation of China (71931004) and Fundamental Research Funds for the Central Universities (2022QKT001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available at https://charls.pku.edu.cn/.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were carried out in accordance with relevant guidelines andregulations. The study was approved by the Ethics committee of Henan Normal University (HNSD-2023BS-0628). Informed consent was obtained fromall subjects and/or their legal guardian(s).\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\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eKey Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, School of Statistics, East China Normal University, Shanghai 200241, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eFaculty of Education，East China Normal University，Shanghai 200062, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eSchool of Economics and Management, East China Normal University, Shanghai 200241, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e4\u003c/sup\u003eDepartment of Mathematical Sciences, Ball State University, Muncie 47304, USA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZeng Y ,Feng Q ,Hesketh T , Christensen K \u0026amp; Vaupel J-W. Survival, disabilities in activities of daily living, and physical and cognitive functioning among the oldest-old in China: a cohort study.The Lancet.2017;389(10079):1619-1629.\u003c/li\u003e\n\u003cli\u003eGao M, Li Y, Zhang S, Gu L, Zhang J, Li Z\u0026amp; Tian D Does an empty nest affect elders\u0026rsquo; health? Empirical evidence from China. International journal of environmental research and public health, 2017, 14(5): 463.\u003c/li\u003e\n\u003cli\u003eBonsang E, Adam S, Perelman S. Does retirement affect cognitive functioning? Journal of Health Economics. 2012;31(3):490-501.\u003c/li\u003e\n\u003cli\u003eAtalay K, Barrett GF, Staneva A. The effect of retirement on elderly cognitive functioning. Journal of Health Economics. 2019;66:37-53.\u003c/li\u003e\n\u003cli\u003eArpino B, Bordone V. Does grandparenting pay off? The effect of child care on grandparents\u0026apos; cognitive functioning. Journal of Marriage \u0026amp; Family. 2014;76(2):337-351.\u003c/li\u003e\n\u003cli\u003eLeimer B, van Ewijk R. Are grandchildren good for you? Well-being and health effects of becoming a grandparent. Social Science \u0026amp; Medicine. 2022;313:115392.\u003c/li\u003e\n\u003cli\u003eRatnakaran B, Shappell AV, Khalid K. Grandparenting and the golden years: Understanding the factors and mental health outcomes of grandparent caregivers in older adults. The American Journal of Geriatric Psychiatry. 2024;32(4):S10.\u003c/li\u003e\n\u003cli\u003eIce GH, Sadruddin AF, Vagedes A, Yogo J, Juma E. Stress associated with caregiving: An examination of the stress process model among Kenyan Luo elders. Social Science \u0026amp; Medicine. 2012;74(12):2020-2027.\u003c/li\u003e\n\u003cli\u003eAtes M. Does grandchild care influence grandparents\u0026rsquo; self-rated health? Evidence from a fixed effects approach. Social Science \u0026amp; Medicine. 2017;190:67-74.\u003c/li\u003e\n\u003cli\u003eXu H. Physical and mental health of Chinese grandparents caring for grandchildren and great-grandparents. Social Science \u0026amp; Medicine. 2019;229:106-116.\u003c/li\u003e\n\u003cli\u003eChoi S-W, Zhang Z. Caring as curing: Grandparenting and depressive symptoms in China. Social Science \u0026amp; Medicine. 2021;289:114452.\u003c/li\u003e\n\u003cli\u003eBaker LA, Silverstein M. Preventive health behaviors among grandmothers raising grandchildren. Journals of Gerontology - Series B Psychological Sciences and Social Sciences. 2008;63(5):S304-S311.\u003c/li\u003e\n\u003cli\u003eDi Gessa G, Glaser K, Tinker A. The impact of caring for grandchildren on the health of grandparents in Europe: A lifecourse approach. Social Science \u0026amp; Medicine. 2016;152:166-175.\u003c/li\u003e\n\u003cli\u003eWang X-L, Cheng J, Guo C-Y, Xu X-R. The implications of childcare on grandparents\u0026apos; health self-management in a chinese elderly population. The International Journal of Health Planning and Management. 2020;35(1):280-289.\u003c/li\u003e\n\u003cli\u003eLiu C, Dai X, Li Y, Li H. Lifestyle adjustment: Influential risk factors in cognitive aging. Advances in Experimental Medicine and Biology. 2023;1419:185-194.\u003c/li\u003e\n\u003cli\u003eLu Y, Bu F-Q, Wang F, Liu L, Zhang S, Wang G, Hu X-Y. Recent advances on the molecular mechanisms of exercise-induced improvements of cognitive dysfunction. Translational Neurodegeneration. 2023;12(1):9.\u003c/li\u003e\n\u003cli\u003eReitz C, Tang M-X, Manly J, Schupf N, Mayeux R, Luchsinger J. Plasma lipid levels in the elderly are not associated with the risk of mild cognitive impairment. Dementia and Geriatric Cognitive Disorders. 2008;25(3):232-237.\u003c/li\u003e\n\u003cli\u003eLin Frank R, Pike James R, Albert Marilyn S, Arnold Michelle, Burgard Sheila, Chisolm Theresa... \u0026amp; Coresh Josef. Hearing intervention versus health education control to reduce cognitive decline in older adults with hearing loss in the USA: a multicentre, randomised controlled trial. Lancet.2023;402(10404):786-797.\u003c/li\u003e\n\u003cli\u003eGatchel JR, Donovan NJ, Locascio JJ, Schultz AP, Becker JA, Chhatwal J, Papp KV, Amariglio RE, Rentz DM, Blacker D, Sperling RA, Johnson KA, Marshall GA. Depressive symptoms and tau accumulation in the inferior temporal lobe and entorhinal cortex in cognitively normal older adults: A pilot study. Journal of Alzheimer\u0026apos;s Disease. 2017;59(3):975-985.\u003c/li\u003e\n\u003cli\u003eCoutinho G, Drummond C, Teldeschi A, Mattos P. Awareness of memory deficits is useful to distinguish between depression and mild cognitive impairment in the elderly. Brazilian Journal of Psychiatry. 2016;38(3):231-234.\u003c/li\u003e\n\u003cli\u003eHou D-c, Sun Y-m, Liu Z-k, Sun H-y, Li Y, Wang R. A longitudinal study of factors associated with cognitive frailty in elderly population based on the health ecology model. Journal of Affective Disorders. 2024;352:410-418.\u003c/li\u003e\n\u003cli\u003eSong Y, Liu Y, Bai X \u0026amp; Yu H. Effects of neighborhood built environment on cognitive function in older adults: a systematic review. BMC Geriatrics. 2024;24(1).\u003c/li\u003e\n\u003cli\u003eMani A, Mullainathan S, Shafir E \u0026amp; Zhao J. Poverty impedes cognitive function. Science ,2013,341(6149):976-980.\u003c/li\u003e\n\u003cli\u003eLeist AK, Novella R, Olivera J. The role of nutrition and literacy on the cognitive functioning of elderly poor individuals. Journal of Aging \u0026amp; Social Policy. 2020;32(3):276-295.\u003c/li\u003e\n\u003cli\u003eSharifi S, Babaei Khorzoughi K, Khaledi-Paveh B, Rahmati M. Association of intergenerational relationship and supports with cognitive performance in older adults: A systematic review. Geriatric Nursing. 2023;52:146-151.\u003c/li\u003e\n\u003cli\u003eJiang T. Mediating effects and moderating effects in causal inference. China Industrial Economics, 2022, 5: 100-120.\u003c/li\u003e\n\u003cli\u003eYi X-j, Zhang L-s, Xu S, Zhou C. Commercial Health Insurance, Precautionary Motivesand Household Consumption:Theoretical Analysis and Empirical Evidence.Journal of Financial Research, 2023, (4): 130-148. (In Chinese)\u003c/li\u003e\n\u003cli\u003eHu Y, Peng W, Ren R, Wang Y \u0026amp; Wang, Ge. Sarcopenia and mild cognitive impairment among elderly adults: the first longitudinal evidence from CHARLS. Journal of cachexia, sarcopenia and muscle, 2022, 13(6): 2944-2952.\u003c/li\u003e\n\u003cli\u003eFlamion A, Missotten P, Marquet M \u0026amp; Adam, S. Impact of contact with grandparents on children\u0026apos;s and adolescents\u0026rsquo; views on the elderly. Child development, 2019, 90(4): 1155-1169.\u003c/li\u003e\n\u003cli\u003eYan Y, Du Y, Li X, Ping W, \u0026amp; Chang Y. Physical function, ADL, and depressive symptoms in Chinese elderly: Evidence from the CHARLS. Frontiers in Public Health, 2023, 11: 1017689.\u003c/li\u003e\n\u003cli\u003eLi Y, Zhao D. Education, neighbourhood context and depression of elderly Chinese. Urban Studies, 2021, 58(16): 3354-3370.\u003c/li\u003e\n\u003cli\u003eLuo J, Cui M. For children or grandchildren?\u0026mdash;The motivation of intergenerational care for the elderly in China. International Journal of Environmental Research and Public Health, 2023, 20(2): 1441.\u003c/li\u003e\n\u003cli\u003eTang S, Xu Y, Li Z, Yang T \u0026amp; Qian D. Does economic support have an impact on the health status of elderly patients with chronic diseases in China?-based on CHARLS (2018) data research. Frontiers in Public Health, 2021, 9: 658830.\u003c/li\u003e\n\u003cli\u003eLiao S, Qi L, Xiong J, Yan J \u0026amp; Wang R. Intergenerational ties in context: Association between caring for grandchildren and cognitive function in older Chinese. International Journal of Environmental Research and Public Health, 2021, 18(1): 21.\u003c/li\u003e\n\u003cli\u003eYin Z-c, Zhang C. The influence of married women\u0026rsquo;s labor force participation on the household saving rate. Economic Research Journal. 2019;54(4):165-181. (In Chinese).\u003c/li\u003e\n\u003cli\u003eB\u0026ouml;hme M H, Persian R, St\u0026ouml;hr T. Alone but better off? Adult child migration and health of elderly parents in Moldova. Journal of Health Economics, 2015, 39: 211-227.\u003c/li\u003e\n\u003cli\u003eWang Y, Zhou C. Promoting social engagement of the elderly to cope with aging of the Chinese population. BioScience Trends, 2020, 14(4): 310-313.\u003c/li\u003e\n\u003cli\u003eHu Y, Wang Z, Wu L. Multidimensional health heterogeneity of Chinese older adults and its determinants. SSM-Population Health, 2023, 24: 101547.\u003c/li\u003e\n\u003cli\u003eZhang Y, Chen G, He Y, Jiang X, Xue C. Social interaction in public spaces and well-being among elderly women: towards age-friendly urban environments. International journal of environmental research and public health, 2022, 19(2): 746.\u003c/li\u003e\n\u003cli\u003ePortegijs E, Lee C, Zhu X. Activity-friendly environments for active aging: The physical, social, and technology environments. Frontiers in public health, 2023, 10: 1080148.\u003c/li\u003e\n\u003cli\u003eTian S-y. Analysis of health-related quality of life of elderly people living alone in Shanghai. Academic Journal of Second Military Medical University, 2018: 258-262.\u003c/li\u003e\n\u003cli\u003eXiang Q-q, LI S-z, Fang W-l, \u0026amp; Chen K-x. Relationship between psychological capital and life quality in elderly people. Chinese Mental Health Journal, 2017: 718-722.\u003c/li\u003e\n\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":"aging, skip-generation caregiving, cognition","lastPublishedDoi":"10.21203/rs.3.rs-4387499/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4387499/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eIn the context of Chinese society, where skip-generation caregiving is a prevalent form of childcare, understanding its implications for the well-being of caregivers, especially concerning cognitive abilities, is imperative. This caregiving arrangement not only alleviates reproductive pressures on younger parents but also promotes societal integration and addresses the challenges posed by an aging population. Despite its benefits, the impact of this form of caregiving on the quality of life of elderly individuals particularly in terms of cognitive function, warrants thorough investigation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo investigate the impact of skip-generation caregiving on the cognitive abilities of the elderly, this study will focus on the quality-of-life impacts and the underlying mechanisms involved.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) for the years 2012, 2015, and 2018,this study constructs an econometric model to assess the relationship between skip-generation caregiving and the cognitive abilities of elderly individuals. Logistic regression models were employed to elucidate the mechanisms through which caregiving influences cognitive outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eRegressions reveal a positive correlation between skip-generation caregiving and improved cognitive abilities in caregivers. Furthermore, a moderate increase in caregiving intensity is associated with sustained cognitive levels. Economic prosperity amplifies the positive effects of caregiving on cognitive health, although the benefits diminish with the caregiver's advancing age. The study highlights three main pathways through which caregiving benefits cognitive function: a reduction in depressive symptoms, increased social interactions, and enhanced intergenerational economic support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eSkip-generation caregiving has been shown to be beneficial for the cognitive health of elderly individuals, with economic status and the economic status of the caregiver and the intensity of caregiving intensity playing significant roles in the extent of these benefits. Tailoring support to meet the specific needs of caregivers is crucial for maximizing the preventive effects against cognitive decline. This research offers valuable insights for policy-making process of developing countries.\u003c/p\u003e","manuscriptTitle":"Can Skip-generation Caregiving Improve the Quality of Life for the Elderly?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-20 17:59:50","doi":"10.21203/rs.3.rs-4387499/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":"77ae83f0-1216-4e58-81bd-f8e434f17a4e","owner":[],"postedDate":"May 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-14T07:24:10+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-20 17:59:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4387499","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4387499","identity":"rs-4387499","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}