The Impact of Long-Term Care Insurance on Frailty among Elderly Individuals: The Mediating Role of Depression Frequency

The Impact of Long-Term Care Insurance on Frailty among Elderly Individuals: The Mediating Role of Depression Frequency | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Impact of Long-Term Care Insurance on Frailty among Elderly Individuals: The Mediating Role of Depression Frequency Sixian Du, Yu Tai, Yaqing Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7678581/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 Long term care insurance (LTCI) has been piloted in three batches for 13 years at all levels in China. Has it achieved the policy goal of improving the disabled and frail elderly and the severely disabled. Using the data of China Health and retirement longitudinal study (Charls) from 2011 to 2018, we found that after the implementation of LTCI, the frailty of the elderly was significantly reduced by -1.779 standard deviations through the multi-phase did model and PSM method. For the elderly with disabilities, the improvement effect of LTCI was more effective, which was consistent with the goal of the policy. Through mechanism analysis, we found that in addition to the physiological level, LTCI can also improve the frailty of the elderly by inhibiting their depression. Health sciences/Health care Health sciences/Medical research Figures Figure 1 Figure 2 Figure 3 Figure 4 I. Background In October 2024, WHO projected that the global population aged 60 and older will increase from 1 billion in 2020 to 1.4 billion by 2030, and will double to 2.1 billion by 2050. Frailty is a clinically recognized condition characterized by diminished physiological reserves and increased vulnerability to adverse health outcomes[1] [2, 3]. Defined as an accumulation of age-related health deficits, frailty is strongly associated with elevated risks of conditions such as stroke, cancer, and myocardial infarction, contributing to increased mortality [4]. The prevalence of frailty among older adults has become a significant global public health concern. The physical frailty phenotype, as proposed by Fried (1977), conceptualizes frailty as a clinical syndrome arising from metabolic dysregulation and impaired stress responses, with key characteristics including fatigue, weakness, slowed motor performance, reduced physical activity, and weight loss. Beyond this physiological perspective, some scholars have expanded the definition of frailty to encompass physical, psychological, and social dimensions[5, 6]. Empirical studies indicate that the overall prevalence of frailty in China is 9.4%, with an additional 45.8% classified as pre-frail, and rates are notably higher in rural areas[7]. Frailty is more prevalent among older adults and is linked to increased risks of adverse health events and elevated healthcare expenditures. Longitudinal studies further highlight the association between frailty and higher all-cause and cause-specific mortality[8], including deaths due to ischemic heart disease, cerebrovascular disease, malignancies, respiratory diseases, and infections. [9] [8]Given these implications, there is growing recognition of the need for preventive and management strategies to mitigate frailty among older adults[10], particularly through physical activity interventions, long-term care services, and preemptive healthcare measures. The rising burden of frailty underscores the urgency of developing robust long-term care insurance (LTCI) systems to address the needs of aging populations. [11] [12] [13]The Netherlands pioneered LTCI legislation with the enactment of the Act on Expenditures on Special Medical Care Costs in 1968. [14] [15]Japan and Germany followed in the 1990s by establishing comprehensive public LTCI systems, with subsequent policy developments observed in the United States, South Korea, and other nations. In China, the introduction of LTCI has been relatively recent. A pilot program was launched in Qingdao in 2012, serving as a model for broader national implementation. In 2016, the Ministry of Human Resources and Social Security (MOHRSS) issued the Guiding Opinions on the Pilot of a Long-Term Care Insurance System, initiating a structured LTCI framework aimed at providing coverage for individuals with significant functional impairments requiring institutional or home-based care. As of 2020, LTCI pilots had expanded to 49 cities, with funding mechanisms primarily sourced from public health insurance pools, supplemented by local government contributions, employer funding, and individual payments. [16] Contribution rates among pilot programs vary, ranging from RMB 30 to RMB 700 per person per year. [17] Evidence suggests that LTCI plays a critical role in improving the health outcomes of frail older adults by facilitating access to personalized care plans, enhancing physical and mental well-being, and reducing disability risks. [18] [19] [20] China's LTCI framework encompasses five core components: basic healthcare services, disease management, functional assistance, complication prevention, and psychosocial support. [21, 22]Empirical research utilizing methods such as difference-in-differences (DID) and propensity score-matched DID (PSM-DID) suggests that LTCI implementation is positively associated with improved self-rated health status and frailty prevention. However, the effects of LTCI may vary across demographic and regional contexts. For instance, studies indicate differential impacts of LTCI on urban versus rural populations[23], and some evidence suggests its role in mitigating depressive symptoms and enhancing psychological well-being among older adults. [24] [25-27] Despite these findings, the specific mechanisms through which LTCI mitigates frailty remain insufficiently explored. While prior studies demonstrate that LTCI implementation significantly reduces the frailty index (FI) among older adults, the causal pathways underlying this effect require further investigation. [28] Key questions remain regarding whether LTCI reduces frailty by alleviating depressive symptoms and whether its impact varies across population subgroups. Addressing these gaps is crucial for optimizing the design and implementation of LTCI policies. This study leverages data from the 2011–2018 China Health and Retirement Longitudinal Study (CHARLS) to examine the impact of LTCI on frailty among older adults. A multi-temporal DID and PSM approach is employed to ensure robust causal inference, using elderly individuals aged 60 and above in pilot cities as the treatment group. Findings indicate that LTCI implementation over a 3–5 year period significantly reduces frailty among insured older adults. The average frailty index declined among those covered by LTCI, reflecting improvements in both physical and mental health. Heterogeneity analysis further reveals that LTCI has a more pronounced impact on frail individuals with disabilities, likely due to the targeted provision of essential care services such as daily assistance and rehabilitation. Additionally, psychological support services embedded within LTCI programs may help alleviate depressive symptoms, contributing to overall improvements in well-being. These findings suggest that LTCI is an effective policy tool for mitigating frailty, particularly among high-risk elderly populations. The remainder of this paper is structured as follows. Section 2 details the institutional framework of China’s LTCI and its implications for frailty reduction. Section 3 describes data sources and the construction of key variables. Section 4 outlines the empirical strategy. Section 5 presents the main findings, including frailty outcomes, mediating mechanisms, heterogeneity analysis, and robustness tests. Section 6 concludes with a discussion of policy implications and future research directions. II. Literature Review and Conceptual Framework A. Review of Long Term Care Insurance Improvement of Frailty Status through Long-Term Care . —Frailty is a multidimensional, dynamic condition characterized by the decline of multiple physiological systems, impairing the ability to cope with daily and acute stressors and increasing all-cause mortality. [29] The Frailty Index (FI), a commonly used measure, is constructed based on accumulated health deficits over an individual's lifespan. [30, 31] Following previous literature, this study constructs the Frailty Index using 28 indicators encompassing chronic diseases (e.g., hypertension, diabetes), functional limitations in daily activities (e.g., dressing, walking, lifting objects), depression (CESD scale), and cognitive function (memory and orientation tests). The FI is primarily based on binary variables (Yes = 1, No = 0), while cognitive function is assessed on a continuous scale (0 to 1). If more than six items are missing, the FI is considered invalid. A frailty index score exceeding 0.25 categorizes an individual as frail. [32] Frailty shares key characteristics with chronic diseases and aging-related conditions, such as being progressive, costly, and negatively impacting health outcomes. [1] [33]The World Health Organization's report on chronic disease care emphasizes the role of community-based healthcare in preventing and improving frailty. Research suggests that interventions such as comprehensive exercise and nutritional support can improve physical frailty in older adults. A review of individuals aged 70 and above demonstrated a positive association between long-term care (LTC) and improved self-rated health. A study in Wisconsin (2009–2010) involving residents aged 65 or older from two nursing homes and an assisted living facility found that LTC facilities significantly improved frailty and health-related quality of life. [18] Furthermore, empirical studies confirm that implementing long-term care insurance (LTCI) enhances self-rated health and cognitive function among elderly individuals, particularly those with physical or cognitive impairments. [34] Health Benefits of Long-Term Care Insurance Pilots in China . —China launched its LTCI pilot program in 2016, with each city designing policies per national guidelines. By 2020, the initiative expanded, adding 14 pilot cities and refining policy regulations. As of 2022, the pilot program covered 49 regions, insuring 169.902 million individuals, benefiting 1.208 million recipients, and supporting 7,679 designated service institutions and 331,000 nursing personnel. LTCI pilot cities primarily adopt home-based care (door-to-door services), institutional care, and community-based care, effectively addressing diverse nursing needs. Benefits focus on professional nursing services and cash compensation for disabled elderly individuals, reducing their economic burden. Most pilot cities maintain a reimbursement rate of approximately 70%, significantly alleviating long-term care costs. The program has also fostered rapid growth in the nursing service sector, increasing the number of service institutions fourfold and expanding the workforce from 30,000 to 330,000. This expansion enhances care quality and efficiency, ensuring better health services for disabled populations and improving their overall well-being. B. Hypotheses Hypothesis 1: LTCI Improves the Frail State of the Elderly . —The Health Production Function framework posits that health outcomes are influenced by medical inputs, behaviors, and environmental factors. It guides resource allocation and policymaking to enhance health outcomes. [35] Medical insurance plays a crucial role in health improvements by increasing service accessibility and reducing out-of-pocket costs. LTCI reduces financial barriers, enabling disabled elderly individuals to receive essential care services, thereby improving physical health and mitigating frailty[18]. Hypothesis 2: LTCI Reduces Depression Frequency in the Elderly . —The Stress Susceptibility Model (or Differential Susceptibility Model) suggests that individuals respond to stressors differently, influencing their health status. Bidirectional Mendelian randomization studies highlight a link between depression and frailty. [36] Research indicates that long-term care residents, especially those with dementia or cognitive impairments, are more prone to depression. LTC services alleviate daily life stressors, such as difficulties in personal care, thereby enhancing coping mechanisms and reducing depressive symptoms. This study hypothesizes that LTC services mitigate depression, indirectly preventing or improving frailty. Hypothesis 3: LTCI More Effectively Improves Frailty in Disabled Elderly Compared to Non-Disabled Elderly . —The Hierarchy of Needs Theory (Maslow, 1943) states that human needs are structured, with unmet needs driving behavior. Disabled elderly individuals face greater challenges at the physiological and safety levels, requiring additional medical care and daily living support. Studies confirm that LTCI services in Japan, including nursing, rehabilitation, and medical care, significantly enhance the quality of life, particularly for disabled elderly individuals. [37]This study hypothesizes that LTCI has a stronger impact on frailty improvement in disabled elderly individuals compared to their non-disabled counterparts, given their higher care needs. III. Data and Methodology A. Data Source and Sample We utilize data from the China Health and Retirement Longitudinal Study (CHARLS) to investigate the impact of Long-Term Care Insurance (LTCI) on frailty improvement and the mechanisms underlying the utilization of inpatient services among middle-aged and older adults. CHARLS initiated its baseline survey in 2011, followed by four waves of follow-up surveys in 2013, 2015, 2018, and 2020. The survey covers 150 counties/districts and 450 villages/urban communities across China, comprising a nationally representative sample of 17,708 individuals from 10,257 households. As this study focuses on older adults, we removed samples with ages below 60 during the observation period. To ensure the purity of the long-term care insurance pilot policy effect estimation, we further excluded samples that joined the survey only in the final wave and were affected by the pilot policy but lacked clear initial policy impact timing. Ultimately, we obtained a four-wave unbalanced panel dataset containing 14,313 valid observations. B. Variables Definition The study incorporates a range of variables to assess factors influencing health outcomes. Control variables include demographic and socioeconomic characteristics such as gender, age group, residence, education, marital status, pension status, employment, hobbies, smoking, and drinking habits. The mediating variable captures self-perceived depression within the past week, reflecting mental health status. Moderating variables include disability status and elderly care reimbursement, which may influence the relationships between key variables. These measures provide a comprehensive framework for analyzing health disparities and social determinants of well-being. Following the existing literature, we include a set of individual-level control variables, as specified in Table 1, to adjust for potential confounding factors. These include demographic, socioeconomic, and health-related characteristics. Table 1—Variable definitions C. Treatment group and control group STable 1 presents the descriptive statistics for the total sample (N = 14,313), the treatment group (N = 811), and the control group (N = 13,502). The treatment group includes individuals covered by long-term care insurance (LTCI), while the control group consists of those who are not covered. In terms of frailty outcomes, the treatment group exhibits a lower frailty index (Mean = 19.77, SD = 13.47) compared to the control group (Mean = 22.12, SD = 14.15). Similarly, the proportion of individuals classified as frail (frailty index > 0.25) is lower in the treatment group (24.8%) relative to the control group (32.8%). With respect to covariates, the treatment group has a higher proportion of males (53.4% vs. 49.9%) and a slightly younger age distribution (Mean age group = 1.787) compared to the control group (Mean = 1.749). Additionally, the treatment group demonstrates higher educational attainment and greater pension coverage. Socioeconomic indicators such as total household income and financial support from children are higher in the treatment group than in the control group. In terms of health-related behaviors and conditions, the treatment group reports lower depression levels, higher rates of commercial insurance coverage, and a lower prevalence of disability. It is important to note that we do not directly observe whether an individual has received LTCI benefits. Our data only provide information on the respondent’s city of residence, the type of medical insurance, and the severity of disability. There is no available information on other eligibility criteria for LTCI benefits (e.g., disability lasting more than six months). Additionally, some insured individuals may not be aware that they are eligible for LTCI benefits, leading them to perceive themselves as part of the control group. Given these limitations, we estimate an Intention-to-Treat (ITT) effect on the treated rather than the traditional Average Treatment Effect on the Treated (ATT) . The ITT approach evaluates the overall treatment effect on the targeted population, irrespective of whether the individual has actually received benefits. This method is considered more conservative, as it may underestimate the conventional treatment effect relative to a scenario where treatment assignment is based on the actual receipt of LTCI benefits Ⅳ. Results A. Main Results In Section 5.1, we will delve into Hypothesis a, as posited in this article, concerning whether the enforcement of Long-Term Care Insurance (LTCI) has positively impacted the frailty index among the elderly population. Specifically, we intend to utilize the frailty index alongside a binary variable that delineates the frailty threshold, conducting our investigation via regression analysis. It is imperative to satisfy the parallel trend assumption as a prerequisite for employing the Difference-in-Differences (DID) methodology. Consequently, we conducted a test for significance at the 95% confidence level. The graphical representations of the parallel trend test results are illustrated in Figures 1 and 2, respectively. As the table3, results of the parallel trend test indicate that, subsequent to the initial phase of Long-Term Care Insurance (LTCI) implementation, irrespective of whether the frailty status of the elderly is measured as a continuous variable or a binary variable, the policy effect diverges significantly from zero at the 5% significance level, thereby fulfilling the criteria for the parallel trend test. From the perspective of the sample period analyzed, the policy effect exhibits a lagged impact, with minimal influence in the immediate period; however, it attains statistical significance after a one-period delay. Table 3—Main regression results Notes:The parentheses indicate the robust standard error, and * *, * *, and * represent the adjoint probabilities p<0.01, * *, and *, respectively p<0.05 、 p<0.1 。 The table below is the same The fundamental regression outcomes presented in Table 1 elucidate that LTCI exerts a notable influence on the health status of elderly individuals. Precisely, in Model (1), the coefficient for LTCI is -2.253 and is statistically significant at the 1% level, suggesting that the enforcement of LTCI markedly decreases the frailty index among the elderly. Similarly, in Model (2), the coefficient for LTCI stands at -1.779 and is also significant at the 1% level, further reinforcing this conclusion. Additionally, the coefficients for LTCI in Models (3) and (4) are -0.0751 and -0.0604, respectively, both significant at the 5% level, indicating the robustness of LTCI's effect on enhancing the health status of elderly individuals. B. PSM-DID In Section 3.2, we will primarily focus on addressing the issue of bias that may arise from sample selection, by matching samples using PSM methods to validate the robustness of the main effect results discussed in the previous section.The specific results are shown in the table below. The distribution of key variables such as age, gender, and education level is more balanced between the treatment and control groups after matching, which helps to reduce bias in model estimation. The continued inclusion of city and year fixed effects ensures control over other potential influencing factors, making the independent impact of LTCI clearer. The PSM-DID analysis in Table 4 further confirms the positive impact of LTCI on the health status of the elderly. Specifically, in model (1), the coefficient of LTCI is -1.821 and significant at the 1% level, indicating that after propensity score matching, the implementation of LTCI still significantly reduces the frailty index of the elderly. In model (2), the coefficient of LTCI is -0.0680 and significant at the 5% level, further supporting this conclusion. Models (3) and (4) also show similar trends, indicating that the PSM-DID method effectively controls selection bias and makes the results more credible. In summary, the PSM-DID results once again confirm the positive role of LTCI in improving the health status of the elderly. Table 4—PSM-DID Results C. Placebo Test To validate the robustness of our baseline findings and address concerns about potential biases from unobserved confounding factors or model misspecification, we conduct placebo tests. In these tests, we randomly assign the treatment status of Long-Term Care Insurance (LTCI) participation across individuals and re-estimate its effects on frailty outcomes. Figure 1 presents the distribution of estimated placebo effects using the continuous frailty index as the dependent variable. The scatter plot shows estimated coefficients and their corresponding p-values from 500 randomized treatment assignments, while the black solid line represents the kernel density of these coefficients. The estimates are symmetrically distributed around zero, and the density function peaks at zero, suggesting no systematic relationship between the placebo treatment and the frailty index. This indicates that the significant effects observed in our main analysis are unlikely to be driven by random chance or model artifacts. Figure 3 shows the placebo test results when the dependent variable is a binary indicator for whether an individual’s frailty index exceeds 0.25, capturing those at higher risk of frailty. Similar to the findings in Figure 4, the placebo estimates are tightly centered around zero, and the kernel density exhibits no significant deviations. The distribution of p-values and coefficients further demonstrates the absence of systematic effects under randomized treatment assignments. Collectively, these two placebo tests provide strong evidence supporting the validity of our empirical strategy and confirm that the observed causal impact of LTCI on reducing frailty is not an artifact of spurious correlations or random variation. D. LTCI and Depression Mental health is also an important aspect of the health status of the elderly and the focus of this section's discussion. Since the frailty index selected did not measure mental health, the previous results could not verify whether LTCI has a positive effect on the mental health of the elderly. Therefore, we selected the frequency of depression in CHARLS as a measure of mental health and constructed the following equation for regression estimation using the results of 1:6 nearest neighbor matching (NNM) in PSM: The regression results are shown in Table 5.Upon controlling for baseline characteristics and other pertinent variables, the findings indicate that Long-Term Care Insurance (LTCI) significantly diminishes the incidence of depression among the elderly in a statistically substantial manner. The results, after adjusting for these variables, reveal that the enforcement of LTCI leads to a reduction in the incidence of depression by 0.114 standard deviations. These outcomes uphold Hypothesis 2, which proposes that the implementation of LTCI not only enhances the physical health of the elderly but also exerts a favorable influence on their psychological well-being. Table 5—Mediation analysis results E Heterogeneity by Subgroups We also examined heterogeneity by other subgroups, including disability status. In order to further explore the impact of LTCI on the health of the elderly, we discussed the heterogeneity of individuals' private purchase of commercial medical insurance and whether they are disabled. On the one hand, we are curious whether LTCI can still improve the health of the elderly when individuals purchase commercial insurance; On the other hand, we also want to verify whether disabled people, a kind of target group of LTCI, benefit more from the policy. As for the specific method, we use Fisher combination test to sample 1000 times and discuss the difference and significance of the coefficient between groups. Table 6 shows the results of two pairs of combined tests. Table 6—Heterogeneity Analysis Ⅴ. Discussion We hypothesized that LTCI services mitigate daily stressors—such as difficulties in personal care—by providing essential support, thus enhancing the elderly's ability to cope with daily life and ultimately reducing their perceived frequency of depression. Unlike previous studies that primarily focused on how LTCI alleviates depressive symptoms, this study expands the perspective to encompass both physical and mental health outcomes. By doing so, it offers a more comprehensive understanding of the value of LTCI and provides a stronger theoretical foundation for policy-making and service optimization. From the perspective of commercial insurance, individuals without such coverage often experience weaker economic security, making LTCI a critical means of accessing essential nursing resources. By enabling these individuals to engage in long-term and regular care interventions—including rehabilitation training and professional medical guidance—LTCI fills gaps in their health maintenance and significantly improves their frailty status. Conversely, for individuals with commercial insurance, the benefits of LTCI may be less pronounced due to the overlap or complementarity between LTCI and commercial insurance products, which could dilute its impact on improving frailty. Regarding disability status, disabled individuals face a higher risk of physical function decline, making frailty a more pressing concern. LTCI offers customized services tailored to their specific needs, such as assistive device adaptation for the physically disabled and cognitive training for those with cognitive impairments. These targeted interventions effectively promote functional recovery and maintenance, leading to significant improvements in frailty status. In contrast, while non-disabled individuals also benefit from LTCI, their lower baseline frailty levels and relatively simpler health challenges result in more modest improvements. Ⅵ. Conclusion This study empirically demonstrates that LTCI significantly reduces frailty among the elderly in China, prevents its progression, and positively influences both physical and mental health by decreasing depression frequency. Unlike previous research that focused solely on the alleviation of depressive symptoms, this study provides a broader perspective on the comprehensive impact of LTCI on elderly health outcomes. The heterogeneity analysis further reveals that individuals without commercial insurance benefit more from LTCI due to its role in bridging economic security gaps, whereas its effects are relatively limited for those with commercial insurance due to product overlap. Similarly, LTCI plays a crucial role in improving frailty among disabled individuals through targeted services, while non-disabled individuals experience relatively smaller improvements. These findings contribute to the existing literature by offering new insights into the mechanisms through which LTCI enhances elderly health. They also provide a valuable basis for optimizing LTCI policies, ensuring precise resource allocation, and maximizing its effectiveness in improving elderly well-being. However, this study has certain limitations. First, as the sample is limited to China, the findings may not be fully generalizable across different cultural and healthcare contexts. Future studies should conduct cross-national and cross-regional comparisons to assess variations in LTCI implementation and outcomes. Second, the study period (2011–2018) limits the ability to capture the long-term, dynamic effects of LTCI. Extending the observation window and establishing long-term monitoring mechanisms would allow for a more comprehensive assessment of LTCI's impact over time. Lastly, while this study explores key mechanisms underlying LTCI’s effects, other potential pathways remain unexamined. Future research should employ interdisciplinary approaches to further investigate the complex interactions between LTCI and elderly health outcomes. By addressing these gaps, future studies can provide stronger empirical support for policy refinement, ensuring that LTCI systems are better tailored to meet the evolving needs of aging populations. Declarations C ontribution S.D. and Y.T. contributed equally to this work and share first authorship. Y.L. contributed substantially to the research and manuscript preparation. Funding This work was supported by the Research Report on the Development Path of Smart Community Healthcare in Jianghan District, Wuhan City (H20230163); the Research on the Current Situation and Development Path of the Integrated Operation of Medical-Nursing Institutions in Hubei Province (H20240117); the Chinese Geriatrics Society 2025 First Batch of Special Topics (Research on Risk Prediction of Macrovascular Complications in Middle-aged and Elderly Patients with Type 2 Diabetes and Hypertension in China Based on Real-world Data. Data availability The datasets generated and/or analysed during the current study are available from the first author or corresponding author on reasonable request; requests can be sent to [email protected] References Alders, Peter and Frederik T. Schut. 2019. "The 2015 Long-Term Care Reform in the Netherlands: Getting the Financial Incentives Right?" Health Policy, 123(3), 312-16. Atkins, J. L.; J. Jylhävä; N. L. Pedersen; P. K. Magnusson; Y. Lu; Y. 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"Aged Care Service Delivery in Japan: Preparing for the Long-Term Care Insurance Scheme." J Aging Soc Policy, 13(2-3), 21-34. Zeng, Lijun; Yue Zhong; Yuxiao Chen; Mei Zhou; Shaoyang Zhao; Jinhui Wu; Birong Dong and Qingyu Dou. 2024. "Effect of Long-Term Care Insurance in a Pilot City of China: Health Benefits among 12,930 Disabled Older Adults." Archives of Gerontology and Geriatrics, 121, 105358. Zeng, X. Z.; N. Jia; L. B. Meng; J. Shi; Y. Y. Li; J. B. Hu; X. Hu; H. Li; H. X. Xu; J. Y. Li, et al. 2022. "A Study on the Prevalence and Related Factors of Frailty and Pre-Frailty in the Older Population with Hypertension in China: A National Cross-Sectional Study." Front Cardiovasc Med, 9, 1057361. Zhang, Kairan; Yujia Liu and Hongwei Hu. 2024. "Multidimensional Poverty and Disability of Older Adults in China: Will Long-Term Care Insurance Make a Difference?" Applied Research in Quality of Life, 19(6), 3439-62. Zhu, J.; D. Zhou; Y. Nie; J. Wang; Y. Yang; D. Chen; M. Yu and Y. Li. 2023. "Assessment of the Bidirectional Causal Association between Frailty and Depression: A Mendelian Randomization Study." J Cachexia Sarcopenia Muscle, 14(5), 2327-34. Additional Declarations No competing interests reported. Supplementary Files APPENDIX.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7678581","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":539011402,"identity":"74ae4975-0174-41c5-8c17-53b568427915","order_by":0,"name":"Sixian Du","email":"","orcid":"","institution":"School of Medicine and Health Management, Huazhong University of Science and Technology，Wuhan, Hubei","correspondingAuthor":false,"prefix":"","firstName":"Sixian","middleName":"","lastName":"Du","suffix":""},{"id":539011403,"identity":"d3eee0d7-02cd-47a3-9629-4c0dbca47528","order_by":1,"name":"Yu Tai","email":"","orcid":"","institution":"School of Economics and Finance, Xi’an Jiaotong University,","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Tai","suffix":""},{"id":539011404,"identity":"39f02480-a9f1-4ffd-a610-d380a3f3711d","order_by":2,"name":"Yaqing Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwElEQVRIiWNgGAWjYJACxo///smxsTcfIF4LswTbAWM+nmMJJFjDw3YgcZ5EjgJxqvln9x6TkOC5k97GkMPA8KNiG2EtEnfOpUkUSDzLbWM4e4Cx58xtIqy5kWMmIWHAnNvG2JfAzNhGhBZ5kBaeBOZ0NmYeA+K0GIC1HDicwMZGrBbDGznG1pINaYZtPGwJB4nyi9yNHMObHxts5OXnPz744EcFMd5nYGCRgLEOEKUeCJg/EKtyFIyCUTAKRigAAJQ2OWIm7OHJAAAAAElFTkSuQmCC","orcid":"","institution":"School of Medicine and Health Management, Huazhong University of Science and Technology，Wuhan, Hubei","correspondingAuthor":true,"prefix":"","firstName":"Yaqing","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2025-09-22 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1","display":"","copyAsset":false,"role":"figure","size":27355,"visible":true,"origin":"","legend":"\u003cp\u003eParallel trend test of Frailty Index\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7678581/v1/c7e162a5fa2984364f10301b.png"},{"id":95229128,"identity":"b0168be4-71c9-4298-91fe-6569e76454f8","added_by":"auto","created_at":"2025-11-05 16:34:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":26077,"visible":true,"origin":"","legend":"\u003cp\u003eParallel trend test of Frailty Index \u0026gt; 0.25\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7678581/v1/85ae166e0e469ad223deb291.png"},{"id":95215901,"identity":"76b924ad-dcc9-40d0-8461-c2bada1b8653","added_by":"auto","created_at":"2025-11-05 15:07:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":80133,"visible":true,"origin":"","legend":"\u003cp\u003ePlacebo Distribution of Estimated Effects on Frailty Index\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7678581/v1/fbf6cece108bca8d770fd7ab.png"},{"id":95215903,"identity":"1d761305-6acc-49d8-9b5d-114acecbec27","added_by":"auto","created_at":"2025-11-05 15:07:42","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47175,"visible":true,"origin":"","legend":"\u003cp\u003ePlacebo Distribution of Estimated Effects on the Probability of Frailty Index \u0026gt; 0.25\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7678581/v1/8ff40e3e2a2ff176b57e9fed.png"},{"id":104520914,"identity":"35e6ba82-612f-48aa-b26c-26567e96a401","added_by":"auto","created_at":"2026-03-12 19:39:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":610247,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7678581/v1/1e79de53-630d-4ccb-94f6-b21ad8a2d6d9.pdf"},{"id":95229118,"identity":"4bc1af13-88c9-4e7f-95aa-5b3e57a216ac","added_by":"auto","created_at":"2025-11-05 16:34:28","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27010,"visible":true,"origin":"","legend":"","description":"","filename":"APPENDIX.docx","url":"https://assets-eu.researchsquare.com/files/rs-7678581/v1/5f859a8199bf72376b53a06e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Long-Term Care Insurance on Frailty among Elderly Individuals: The Mediating Role of Depression Frequency","fulltext":[{"header":"I. Background","content":"\u003cp\u003eIn October 2024, WHO projected that the global population aged 60 and older will increase from 1 billion in 2020 to 1.4 billion by 2030, and will double to 2.1 billion by 2050. Frailty is a clinically recognized condition characterized by diminished physiological reserves and increased vulnerability to adverse health outcomes[1] [2, 3]. Defined as an accumulation of age-related health deficits, frailty is strongly associated with elevated risks of conditions such as stroke, cancer, and myocardial infarction, contributing to increased mortality [4]. The prevalence of frailty among older adults has become a significant global public health concern. The physical frailty phenotype, as proposed by Fried (1977), conceptualizes frailty as a clinical syndrome arising from metabolic dysregulation and impaired stress responses, with key characteristics including fatigue, weakness, slowed motor performance, reduced physical activity, and weight loss. Beyond this physiological perspective, some scholars have expanded the definition of frailty to encompass physical, psychological, and social dimensions[5, 6].\u003c/p\u003e\n\u003cp\u003eEmpirical studies indicate that the overall prevalence of frailty in China is 9.4%, with an additional 45.8% classified as pre-frail, and rates are notably higher in rural areas[7]. Frailty is more prevalent among older adults and is linked to increased risks of adverse health events and elevated healthcare expenditures. Longitudinal studies further highlight the association between frailty and higher all-cause and cause-specific mortality[8], including deaths due to ischemic heart disease, cerebrovascular disease, malignancies, respiratory diseases, and infections. [9] [8]Given these implications, there is growing recognition of the need for preventive and management strategies to mitigate frailty among older adults[10], particularly through physical activity interventions, long-term care services, and preemptive healthcare measures.\u003c/p\u003e\n\u003cp\u003eThe rising burden of frailty underscores the urgency of developing robust long-term care insurance (LTCI) systems to address the needs of aging populations. [11] [12] [13]The Netherlands pioneered LTCI legislation with the enactment of the Act on Expenditures on Special Medical Care Costs in 1968. [14] [15]Japan and Germany followed in the 1990s by establishing comprehensive public LTCI systems, with subsequent policy developments observed in the United States, South Korea, and other nations.\u003c/p\u003e\n\u003cp\u003eIn China, the introduction of LTCI has been relatively recent. A pilot program was launched in Qingdao in 2012, serving as a model for broader national implementation. In 2016, the Ministry of Human Resources and Social Security (MOHRSS) issued the Guiding Opinions on the Pilot of a Long-Term Care Insurance System, initiating a structured LTCI framework aimed at providing coverage for individuals with significant functional impairments requiring institutional or home-based care. As of 2020, LTCI pilots had expanded to 49 cities, with funding mechanisms primarily sourced from public health insurance pools, supplemented by local government contributions, employer funding, and individual payments. [16] Contribution rates among pilot programs vary, ranging from RMB 30 to RMB 700 per person per year. [17]\u003c/p\u003e\n\u003cp\u003eEvidence suggests that LTCI plays a critical role in improving the health outcomes of frail older adults by facilitating access to personalized care plans, enhancing physical and mental well-being, and reducing disability risks. [18] [19] [20] China's LTCI framework encompasses five core components: basic healthcare services, disease management, functional assistance, complication prevention, and psychosocial support. [21, 22]Empirical research utilizing methods such as difference-in-differences (DID) and propensity score-matched DID (PSM-DID) suggests that LTCI implementation is positively associated with improved self-rated health status and frailty prevention. However, the effects of LTCI may vary across demographic and regional contexts. For instance, studies indicate differential impacts of LTCI on urban versus rural populations[23], and some evidence suggests its role in mitigating depressive symptoms and enhancing psychological well-being among older adults. [24] [25-27]\u003c/p\u003e\n\u003cp\u003eDespite these findings, the specific mechanisms through which LTCI mitigates frailty remain insufficiently explored. While prior studies demonstrate that LTCI implementation significantly reduces the frailty index (FI) among older adults, the causal pathways underlying this effect require further investigation. [28] Key questions remain regarding whether LTCI reduces frailty by alleviating depressive symptoms and whether its impact varies across population subgroups. Addressing these gaps is crucial for optimizing the design and implementation of LTCI policies.\u003c/p\u003e\n\u003cp\u003eThis study leverages data from the 2011–2018 China Health and Retirement Longitudinal Study (CHARLS) to examine the impact of LTCI on frailty among older adults. A multi-temporal DID and PSM approach is employed to ensure robust causal inference, using elderly individuals aged 60 and above in pilot cities as the treatment group. Findings indicate that LTCI implementation over a 3–5 year period significantly reduces frailty among insured older adults. The average frailty index declined among those covered by LTCI, reflecting improvements in both physical and mental health. Heterogeneity analysis further reveals that LTCI has a more pronounced impact on frail individuals with disabilities, likely due to the targeted provision of essential care services such as daily assistance and rehabilitation. Additionally, psychological support services embedded within LTCI programs may help alleviate depressive symptoms, contributing to overall improvements in well-being. These findings suggest that LTCI is an effective policy tool for mitigating frailty, particularly among high-risk elderly populations.\u003c/p\u003e\n\u003cp\u003eThe remainder of this paper is structured as follows. Section 2 details the institutional framework of China’s LTCI and its implications for frailty reduction. Section 3 describes data sources and the construction of key variables. Section 4 outlines the empirical strategy. Section 5 presents the main findings, including frailty outcomes, mediating mechanisms, heterogeneity analysis, and robustness tests. Section 6 concludes with a discussion of policy implications and future research directions.\u003c/p\u003e"},{"header":"II. Literature Review and Conceptual Framework","content":"\u003ch2\u003eA. Review of Long Term Care Insurance\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eImprovement of Frailty Status through Long-Term Care\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e—Frailty is a multidimensional, dynamic condition characterized by the decline of multiple physiological systems, impairing the ability to cope with daily and acute stressors and increasing all-cause mortality. [29] The Frailty Index (FI), a commonly used measure, is constructed based on accumulated health deficits over an individual's lifespan. [30, 31]\u003c/p\u003e\n\u003cp\u003eFollowing previous literature, this study constructs the Frailty Index using 28 indicators encompassing chronic diseases (e.g., hypertension, diabetes), functional limitations in daily activities (e.g., dressing, walking, lifting objects), depression (CESD scale), and cognitive function (memory and orientation tests). The FI is primarily based on binary variables (Yes = 1, No = 0), while cognitive function is assessed on a continuous scale (0 to 1). If more than six items are missing, the FI is considered invalid. A frailty index score exceeding 0.25 categorizes an individual as frail. [32]\u003c/p\u003e\n\u003cp\u003eFrailty shares key characteristics with chronic diseases and aging-related conditions, such as being progressive, costly, and negatively impacting health outcomes. [1] [33]The World Health Organization's report on chronic disease care emphasizes the role of community-based healthcare in preventing and improving frailty. Research suggests that interventions such as comprehensive exercise and nutritional support can improve physical frailty in older adults. A review of individuals aged 70 and above demonstrated a positive association between long-term care (LTC) and improved self-rated health. A study in Wisconsin (2009–2010) involving residents aged 65 or older from two nursing homes and an assisted living facility found that LTC facilities significantly improved frailty and health-related quality of life. [18] Furthermore, empirical studies confirm that implementing long-term care insurance (LTCI) enhances self-rated health and cognitive function among elderly individuals, particularly those with physical or cognitive impairments. [34]\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHealth Benefits of Long-Term Care Insurance Pilots in China\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e—China launched its LTCI pilot program in 2016, with each city designing policies per national guidelines. By 2020, the initiative expanded, adding 14 pilot cities and refining policy regulations. As of 2022, the pilot program covered 49 regions, insuring 169.902 million individuals, benefiting 1.208 million recipients, and supporting 7,679 designated service institutions and 331,000 nursing personnel.\u003c/p\u003e\n\u003cp\u003eLTCI pilot cities primarily adopt home-based care (door-to-door services), institutional care, and community-based care, effectively addressing diverse nursing needs. Benefits focus on professional nursing services and cash compensation for disabled elderly individuals, reducing their economic burden. Most pilot cities maintain a reimbursement rate of approximately 70%, significantly alleviating long-term care costs. The program has also fostered rapid growth in the nursing service sector, increasing the number of service institutions fourfold and expanding the workforce from 30,000 to 330,000. This expansion enhances care quality and efficiency, ensuring better health services for disabled populations and improving their overall well-being.\u003c/p\u003e\n\u003ch2\u003eB. Hypotheses\u003c/h2\u003e\n\u003cp\u003e\u003cem\u003eHypothesis 1: LTCI Improves the Frail State of the Elderly\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e—The Health Production Function framework posits that health outcomes are influenced by medical inputs, behaviors, and environmental factors. It guides resource allocation and policymaking to enhance health outcomes. [35] Medical insurance plays a crucial role in health improvements by increasing service accessibility and reducing out-of-pocket costs. LTCI reduces financial barriers, enabling disabled elderly individuals to receive essential care services, thereby improving physical health and mitigating frailty[18].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHypothesis 2: LTCI Reduces Depression Frequency in the Elderly\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e—The Stress Susceptibility Model (or Differential Susceptibility Model) suggests that individuals respond to stressors differently, influencing their health status. Bidirectional Mendelian randomization studies highlight a link between depression and frailty. [36] Research indicates that long-term care residents, especially those with dementia or cognitive impairments, are more prone to depression. LTC services alleviate daily life stressors, such as difficulties in personal care, thereby enhancing coping mechanisms and reducing depressive symptoms. This study hypothesizes that LTC services mitigate depression, indirectly preventing or improving frailty.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHypothesis 3: LTCI More Effectively Improves Frailty in Disabled Elderly Compared to Non-Disabled Elderly\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e—The Hierarchy of Needs Theory (Maslow, 1943) states that human needs are structured, with unmet needs driving behavior. Disabled elderly individuals face greater challenges at the physiological and safety levels, requiring additional medical care and daily living support. Studies confirm that LTCI services in Japan, including nursing, rehabilitation, and medical care, significantly enhance the quality of life, particularly for disabled elderly individuals. [37]This study hypothesizes that LTCI has a stronger impact on frailty improvement in disabled elderly individuals compared to their non-disabled counterparts, given their higher care needs.\u003c/p\u003e"},{"header":"III. Data and Methodology","content":"\u003ch2\u003eA.\u0026nbsp;Data Source and Sample\u003c/h2\u003e\n\u003cp\u003eWe utilize data from the China Health and Retirement Longitudinal Study (CHARLS) to investigate the impact of Long-Term Care Insurance (LTCI) on frailty improvement and the mechanisms underlying the utilization of inpatient services among middle-aged and older adults. CHARLS initiated its baseline survey in 2011, followed by four waves of follow-up surveys in 2013, 2015, 2018, and 2020. The survey covers 150 counties/districts and 450 villages/urban communities across China, comprising a nationally representative sample of 17,708 individuals from 10,257 households.\u003c/p\u003e\n\u003cp\u003eAs this study focuses on older adults, we removed samples with ages below 60 during the observation period. To ensure the purity of the long-term care insurance pilot policy effect estimation, we further excluded samples that joined the survey only in the final wave and were affected by the pilot policy but lacked clear initial policy impact timing. Ultimately, we obtained a four-wave unbalanced panel dataset containing 14,313 valid observations.\u003c/p\u003e\n\u003ch2\u003eB.\u0026nbsp;Variables Definition\u003c/h2\u003e\n\u003cp\u003eThe study incorporates a range of variables to assess factors influencing health outcomes. Control variables include demographic and socioeconomic characteristics such as gender, age group, residence, education, marital status, pension status, employment, hobbies, smoking, and drinking habits. The mediating variable captures self-perceived depression within the past week, reflecting mental health status. Moderating variables include disability status and elderly care reimbursement, which may influence the relationships between key variables. These measures provide a comprehensive framework for analyzing health disparities and social determinants of well-being. Following the existing literature, we include a set of individual-level control variables, as specified in Table 1, to adjust for potential confounding factors. These include demographic, socioeconomic, and health-related characteristics.\u003c/p\u003e\n\u003cp\u003eTable 1\u0026mdash;Variable definitions\u003c/p\u003e\n\u003ch2\u003eC.\u0026nbsp;Treatment group and control group\u003c/h2\u003e\n\u003cp\u003eSTable 1 presents the descriptive statistics for the total sample (N = 14,313), the treatment group (N = 811), and the control group (N = 13,502). The treatment group includes individuals covered by long-term care insurance (LTCI), while the control group consists of those who are not covered.\u003c/p\u003e\n\u003cp\u003eIn terms of frailty outcomes, the treatment group exhibits a lower frailty index (Mean = 19.77, SD = 13.47) compared to the control group (Mean = 22.12, SD = 14.15). Similarly, the proportion of individuals classified as frail (frailty index \u0026gt; 0.25) is lower in the treatment group (24.8%) relative to the control group (32.8%).\u003c/p\u003e\n\u003cp\u003eWith respect to covariates, the treatment group has a higher proportion of males (53.4% vs. 49.9%) and a slightly younger age distribution (Mean age group = 1.787) compared to the control group (Mean = 1.749). Additionally, the treatment group demonstrates higher educational attainment and greater pension coverage. Socioeconomic indicators such as total household income and financial support from children are higher in the treatment group than in the control group. In terms of health-related behaviors and conditions, the treatment group reports lower depression levels, higher rates of commercial insurance coverage, and a lower prevalence of disability.\u003c/p\u003e\n\u003cp\u003eIt is important to note that we do not directly observe whether an individual has received LTCI benefits. Our data only provide information on the respondent\u0026rsquo;s city of residence, the type of medical insurance, and the severity of disability. There is no available information on other eligibility criteria for LTCI benefits (e.g., disability lasting more than six months). Additionally, some insured individuals may not be aware that they are eligible for LTCI benefits, leading them to perceive themselves as part of the control group.\u003c/p\u003e\n\u003cp\u003eGiven these limitations, we estimate an Intention-to-Treat (ITT) effect on the treated rather than the traditional Average Treatment Effect on the Treated (ATT) . The ITT approach evaluates the overall treatment effect on the targeted population, irrespective of whether the individual has actually received benefits. This method is considered more conservative, as it may underestimate the conventional treatment effect relative to a scenario where treatment assignment is based on the actual receipt of LTCI benefits\u003c/p\u003e"},{"header":"Ⅳ. Results","content":"\u003ch2\u003eA.\u0026nbsp;Main Results\u003c/h2\u003e\n\u003cp\u003eIn Section 5.1, we will delve into Hypothesis a, as posited in this article, concerning whether the enforcement of Long-Term Care Insurance (LTCI) has positively impacted the frailty index among the elderly population. Specifically, we intend to utilize the frailty index alongside a binary variable that delineates the frailty threshold, conducting our investigation via regression analysis.\u003c/p\u003e\n\u003cp\u003eIt is imperative to satisfy the parallel trend assumption as a prerequisite for employing the Difference-in-Differences (DID) methodology. Consequently, we conducted a test for significance at the 95% confidence level. The graphical representations of the parallel trend test results are illustrated in Figures 1 and 2, respectively.\u003c/p\u003e\n\u003cp\u003eAs the table3, results of the parallel trend test indicate that, subsequent to the initial phase of Long-Term Care Insurance (LTCI) implementation, irrespective of whether the frailty status of the elderly is measured as a continuous variable or a binary variable, the policy effect diverges significantly from zero at the 5% significance level, thereby fulfilling the criteria for the parallel trend test. From the perspective of the sample period analyzed, the policy effect exhibits a lagged impact, with minimal influence in the immediate period; however, it attains statistical significance after a one-period delay.\u003c/p\u003e\n\u003cp\u003eTable 3\u0026mdash;Main regression results\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\u003c/div\u003e\n\u003cp\u003e\u003cem\u003eNotes:The parentheses indicate the robust standard error, and * *, * *, and * represent the adjoint probabilities p\u0026lt;0.01, * *, and *, respectively p\u0026lt;0.05\u003c/em\u003e\u003cem\u003e、\u003c/em\u003e\u003cem\u003ep\u0026lt;0.1\u003c/em\u003e\u003cem\u003e。\u003c/em\u003e\u003cem\u003e\u0026nbsp;The table below is the same\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe fundamental regression outcomes presented in Table 1 elucidate that LTCI exerts a notable influence on the health status of elderly individuals. Precisely, in Model (1), the coefficient for LTCI is -2.253 and is statistically significant at the 1% level, suggesting that the enforcement of LTCI markedly decreases the frailty index among the elderly. Similarly, in Model (2), the coefficient for LTCI stands at -1.779 and is also significant at the 1% level, further reinforcing this conclusion. Additionally, the coefficients for LTCI in Models (3) and (4) are -0.0751 and -0.0604, respectively, both significant at the 5% level, indicating the robustness of LTCI\u0026apos;s effect on enhancing the health status of elderly individuals.\u003c/p\u003e\n\u003ch2\u003eB.\u0026nbsp;PSM-DID\u003c/h2\u003e\n\u003cp\u003eIn Section 3.2, we will primarily focus on addressing the issue of bias that may arise from sample selection, by matching samples using PSM methods to validate the robustness of the main effect results discussed in the previous section.The specific results are shown in the table below.\u003c/p\u003e\n\u003cp\u003eThe distribution of key variables such as age, gender, and education level is more balanced between the treatment and control groups after matching, which helps to reduce bias in model estimation. The continued inclusion of city and year fixed effects ensures control over other potential influencing factors, making the independent impact of LTCI clearer.\u003c/p\u003e\n\u003cp\u003eThe PSM-DID analysis in\u0026nbsp;Table\u0026nbsp;4\u0026nbsp;further confirms the positive impact of LTCI on the health status of the elderly. Specifically, in model (1), the coefficient of LTCI is -1.821 and significant at the 1% level, indicating that after propensity score matching, the implementation of LTCI still significantly reduces the frailty index of the elderly. In model (2), the coefficient of LTCI is -0.0680 and significant at the 5% level, further supporting this conclusion. Models (3) and (4) also show similar trends, indicating that the PSM-DID method effectively controls selection bias and makes the results more credible.\u003c/p\u003e\n\u003cp\u003eIn summary, the PSM-DID results once again confirm the positive role of LTCI in improving the health status of the elderly.\u003c/p\u003e\n\u003cp\u003eTable 4\u0026mdash;PSM-DID Results\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\u003c/div\u003e\n\u003ch2\u003eC. Placebo Test\u003c/h2\u003e\n\u003cp\u003eTo validate the robustness of our baseline findings and address concerns about potential biases from unobserved confounding factors or model misspecification, we conduct placebo tests. In these tests, we randomly assign the treatment status of Long-Term Care Insurance (LTCI) participation across individuals and re-estimate its effects on frailty outcomes. Figure 1 presents the distribution of estimated placebo effects using the continuous frailty index as the dependent variable. The scatter plot shows estimated coefficients and their corresponding p-values from 500 randomized treatment assignments, while the black solid line represents the kernel density of these coefficients. The estimates are symmetrically distributed around zero, and the density function peaks at zero, suggesting no systematic relationship between the placebo treatment and the frailty index. This indicates that the significant effects observed in our main analysis are unlikely to be driven by random chance or model artifacts.\u003c/p\u003e\n\u003cp\u003eFigure 3 shows the placebo test results when the dependent variable is a binary indicator for whether an individual\u0026rsquo;s frailty index exceeds 0.25, capturing those at higher risk of frailty. Similar to the findings in Figure 4, the placebo estimates are tightly centered around zero, and the kernel density exhibits no significant deviations. The distribution of p-values and coefficients further demonstrates the absence of systematic effects under randomized treatment assignments. Collectively, these two placebo tests provide strong evidence supporting the validity of our empirical strategy and confirm that the observed causal impact of LTCI on reducing frailty is not an artifact of spurious correlations or random variation.\u003c/p\u003e\n\u003ch2\u003eD. LTCI and Depression\u003c/h2\u003e\n\u003cp\u003eMental health is also an important aspect of the health status of the elderly and the focus of this section\u0026apos;s discussion. Since the frailty index selected did not measure mental health, the previous results could not verify whether LTCI has a positive effect on the mental health of the elderly. Therefore, we selected the frequency of depression in CHARLS as a measure of mental health and constructed the following equation for regression estimation using the results of 1:6 nearest neighbor matching (NNM) in PSM:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003eThe regression results are shown in Table 5.Upon controlling for baseline characteristics and other pertinent variables, the findings indicate that Long-Term Care Insurance (LTCI) significantly diminishes the incidence of depression among the elderly in a statistically substantial manner. The results, after adjusting for these variables, reveal that the enforcement of LTCI leads to a reduction in the incidence of depression by 0.114 standard deviations. These outcomes uphold Hypothesis 2, which proposes that the implementation of LTCI not only enhances the physical health of the elderly but also exerts a favorable influence on their psychological well-being.\u003c/p\u003e\n\u003cp\u003eTable 5\u0026mdash;Mediation analysis results\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\u003c/div\u003e\n\u003ch2\u003eE Heterogeneity by \u0026nbsp;Subgroups\u003c/h2\u003e\n\u003cp\u003eWe also examined heterogeneity by other subgroups, including disability status. In order to further explore the impact of LTCI on the health of the elderly, we discussed the heterogeneity of individuals\u0026apos; private purchase of commercial medical insurance and whether they are disabled. On the one hand, we are curious whether LTCI can still improve the health of the elderly when individuals purchase commercial insurance; On the other hand, we also want to verify whether disabled people, a kind of target group of LTCI, benefit more from the policy. As for the specific method, we use Fisher combination test to sample 1000 times and discuss the difference and significance of the coefficient between groups. Table 6 shows the results of two pairs of combined tests.\u003c/p\u003e\n\u003cp\u003eTable 6\u0026mdash;Heterogeneity Analysis\u003c/p\u003e\n\u003cdiv align=\"Left\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Ⅴ. Discussion","content":"\u003cp\u003eWe hypothesized that LTCI services mitigate daily stressors\u0026mdash;such as difficulties in personal care\u0026mdash;by providing essential support, thus enhancing the elderly's ability to cope with daily life and ultimately reducing their perceived frequency of depression. Unlike previous studies that primarily focused on how LTCI alleviates depressive symptoms, this study expands the perspective to encompass both physical and mental health outcomes. By doing so, it offers a more comprehensive understanding of the value of LTCI and provides a stronger theoretical foundation for policy-making and service optimization.\u003c/p\u003e\u003cp\u003eFrom the perspective of commercial insurance, individuals without such coverage often experience weaker economic security, making LTCI a critical means of accessing essential nursing resources. By enabling these individuals to engage in long-term and regular care interventions\u0026mdash;including rehabilitation training and professional medical guidance\u0026mdash;LTCI fills gaps in their health maintenance and significantly improves their frailty status. Conversely, for individuals with commercial insurance, the benefits of LTCI may be less pronounced due to the overlap or complementarity between LTCI and commercial insurance products, which could dilute its impact on improving frailty.\u003c/p\u003e\u003cp\u003eRegarding disability status, disabled individuals face a higher risk of physical function decline, making frailty a more pressing concern. LTCI offers customized services tailored to their specific needs, such as assistive device adaptation for the physically disabled and cognitive training for those with cognitive impairments. These targeted interventions effectively promote functional recovery and maintenance, leading to significant improvements in frailty status. In contrast, while non-disabled individuals also benefit from LTCI, their lower baseline frailty levels and relatively simpler health challenges result in more modest improvements.\u003c/p\u003e"},{"header":"Ⅵ. Conclusion","content":"\u003cp\u003eThis study empirically demonstrates that LTCI significantly reduces frailty among the elderly in China, prevents its progression, and positively influences both physical and mental health by decreasing depression frequency. Unlike previous research that focused solely on the alleviation of depressive symptoms, this study provides a broader perspective on the comprehensive impact of LTCI on elderly health outcomes. The heterogeneity analysis further reveals that individuals without commercial insurance benefit more from LTCI due to its role in bridging economic security gaps, whereas its effects are relatively limited for those with commercial insurance due to product overlap. Similarly, LTCI plays a crucial role in improving frailty among disabled individuals through targeted services, while non-disabled individuals experience relatively smaller improvements.\u003c/p\u003e\u003cp\u003eThese findings contribute to the existing literature by offering new insights into the mechanisms through which LTCI enhances elderly health. They also provide a valuable basis for optimizing LTCI policies, ensuring precise resource allocation, and maximizing its effectiveness in improving elderly well-being.\u003c/p\u003e\u003cp\u003eHowever, this study has certain limitations. First, as the sample is limited to China, the findings may not be fully generalizable across different cultural and healthcare contexts. Future studies should conduct cross-national and cross-regional comparisons to assess variations in LTCI implementation and outcomes. Second, the study period (2011\u0026ndash;2018) limits the ability to capture the long-term, dynamic effects of LTCI. Extending the observation window and establishing long-term monitoring mechanisms would allow for a more comprehensive assessment of LTCI's impact over time. Lastly, while this study explores key mechanisms underlying LTCI\u0026rsquo;s effects, other potential pathways remain unexamined. Future research should employ interdisciplinary approaches to further investigate the complex interactions between LTCI and elderly health outcomes.\u003c/p\u003e\u003cp\u003eBy addressing these gaps, future studies can provide stronger empirical support for policy refinement, ensuring that LTCI systems are better tailored to meet the evolving needs of aging populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003cstrong\u003eontribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.D. and Y.T. contributed equally to this work and share first authorship. Y.L. contributed substantially to the research and manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Research Report on the Development Path of Smart Community Healthcare in Jianghan District, Wuhan City (H20230163); the Research on the Current Situation and Development Path of the Integrated Operation of Medical-Nursing Institutions in Hubei Province (H20240117); the Chinese Geriatrics Society 2025 First Batch of Special Topics (Research on Risk Prediction of Macrovascular Complications in Middle-aged and Elderly Patients with Type 2 Diabetes and Hypertension in China Based on Real-world Data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analysed during the current study are available from the first author or corresponding author on reasonable request; requests can be sent to [email protected]\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAlders, Peter and Frederik T. 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Meng; J. Shi; Y. Y. Li; J. B. Hu; X. Hu; H. Li; H. X. Xu; J. Y. Li, et al. 2022. \u0026quot;A Study on the Prevalence and Related Factors of Frailty and Pre-Frailty in the Older Population with Hypertension in China: A National Cross-Sectional Study.\u0026quot; Front Cardiovasc Med, 9, 1057361.\u003c/li\u003e\n \u003cli\u003eZhang, Kairan; Yujia Liu and Hongwei Hu. 2024. \u0026quot;Multidimensional Poverty and Disability of Older Adults in China: Will Long-Term Care Insurance Make a Difference?\u0026quot; Applied Research in Quality of Life, 19(6), 3439-62.\u003c/li\u003e\n \u003cli\u003eZhu, J.; D. Zhou; Y. Nie; J. Wang; Y. Yang; D. Chen; M. Yu and Y. Li. 2023. \u0026quot;Assessment of the Bidirectional Causal Association between Frailty and Depression: A Mendelian Randomization Study.\u0026quot; J Cachexia Sarcopenia Muscle, 14(5), 2327-34.\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":"","lastPublishedDoi":"10.21203/rs.3.rs-7678581/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7678581/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLong term care insurance (LTCI) has been piloted in three batches for 13 years at all levels in China. Has it achieved the policy goal of improving the disabled and frail elderly and the severely disabled. Using the data of China Health and retirement longitudinal study (Charls) from 2011 to 2018, we found that after the implementation of LTCI, the frailty of the elderly was significantly reduced by -1.779 standard deviations through the multi-phase did model and PSM method. For the elderly with disabilities, the improvement effect of LTCI was more effective, which was consistent with the goal of the policy. Through mechanism analysis, we found that in addition to the physiological level, LTCI can also improve the frailty of the elderly by inhibiting their depression.\u003c/p\u003e","manuscriptTitle":"The Impact of Long-Term Care Insurance on Frailty among Elderly Individuals: The Mediating Role of Depression Frequency","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-05 15:07:37","doi":"10.21203/rs.3.rs-7678581/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":"51a72f2a-58cc-48f1-9099-e225b5fe8bb0","owner":[],"postedDate":"November 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57320205,"name":"Health sciences/Health care"},{"id":57320206,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-03-12T19:39:14+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-05 15:07:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7678581","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7678581","identity":"rs-7678581","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}