Skip to main content
Download PDF

Association between catastrophic health expenditure and mental health among elderly in China: the potential role of income and social activity

BMC Geriatrics volume 25, Article number: 231 (2025) Cite this article

Abstract

Background

Little is known about the association between catastrophic health expenditure (CHE) and mental health in elderly population and its potential moderators. This study examined the relationship between CHE and depressive symptoms in Chinese older persons and its difference between groups of different income level and social activity engagement.

Methods

We employed data from the 4 waves (2011, 2013, 2015, and 2018, N = 15,406) of the China Health and Retirement Longitudinal Study (CHARLS). A linear mixed model was used to examine the association between depressive symptoms and CHE, and interaction terms were involved in the model to examine the moderating role of social activity and income levels.

Results

Significant correlations have been shown between CHE and depressive symptoms(coefficient = 0.363, P < 0.05), such association was more pronounced in socially inactive (P = 0.034, Difference = 0.37, interaction terms (social activity*CHE: -1.189) or low-income seniors (P < 0.001, Difference = 0.77, interaction terms (medium income*CHE: -0.594, P < 0.05, high income*CHE: -0.667, P < 0.01), and especially in socially inactive and low-income seniors (P < 0.001, Difference = 0.93, interaction terms (high income*CHE*social acitivity: 1.132, P < 0.05). Even after increasing the threshold of CHE to 20% and 25%, similar pattern was observed.

Conclusions

This study suggest a positive association between CHE event and depressive symptoms, as well as the protective effect of advantaged financial status and engagement of social activity. Our finding provide empirical evidence to call for urgent action for government and public health authorities, to address the high medical expenditure, psychological stress among elderly, especially for low-income households or elderly living alone.

Peer Review reports

Introduction

Depression, as one of the most common mental health problems across the world, has led to series of adverse health outcomes, imposing substantial burdens on individuals, families and society [1]. Nevertheless, the impact of depression on the elderly population may be more severe compared to younger individuals due to the deterioration of activities of daily living, the presence of multimorbidity, increasing social isolation and negative life events such as the death of spouse [2]. Currently, depression has become a major public health concern in China, and with the rapid population aging, geriatric depression has been climbing dramatically [3]. Previous studies suggested that the prevalence of depression in the middle-aged and older adult population in China ranges from 17.4 to 46.15% [3, 4]. Therefore, the detection of risk factors for early and precise prevention and intervention is in urgent need for the alleviation of such a severe mental health challenge.

Catastrophic health expenditure (CHE) refers to the case when out-of-pocket (OOP) health payments exceeds a certain threshold share of a household’s total or non-food expenditure [5]. It is a global issue that have significant impact on universal health coverage and poverty reduction. More than 200 million people across the world suffered from CHE, and half of them were impoverished due to the OOP medical expenditure [6]. In China, although the CHE rate declined in recent years, from 13.58% in 2010 to 11.06% in 2016, it remains at a relatively high level from a global perspective [7]. As a major adverse event, CHE imposes heavy financial burden and stress on households, which may potentially lead to mental health problems, such as depressive symptoms, anxiety, etc [5]. In comparison to other population group, the elderly population is more vulnerable and faces a higher risk of CHE [8]. The consequent financial hardship, together with the deteriorated health conditions and the loneliness that frequently occurred during late life will further elevate the risk of depression [9].

In the past few years, increasing evidence has emerged to support the impact of socio-economic factors on mental health outcomes [10]. Decomposition analyses suggested that socio-economic conditions make the largest contribution to the mental health inequality between the rich and the poor [11]. Apparently, socio-economic disadvantaged groups are always disproportionately suffered from mental disorders, while those with higher income levels have better access to healthcare resources and lower financial pressure when encountering high medical expenses, thus the occurrence of catastrophic health expenditure could be further reduced [12]. As previous research suggested, catastrophic health expenditure (CHE) exacerbates mental health issues through socioeconomic, psychological, and biological mechanisms: financial strain triggers chronic stress and feelings of helplessness, while prolonged economic hardship activates physiological stress responses like elevated cortisol and inflammation, contributing to depression and anxiety [13]. Vulnerable populations, such as older adults and low-income households, are disproportionately affected due to limited financial buffers and healthcare access [14, 15]. These pathways highlight the interconnectedness of economic deprivation and mental health deterioration. Additionally, studies have shown that low family connections and social support are key predictors of psychological anxiety and depressive symptoms among older adults [16, 17], economic status moderates the mental health impact of catastrophic health expenditure (CHE) by buffering financial strain, while activity theory suggests that social activities buffer the mental health impact of catastrophic health expenditure (CHE) in older adults by fostering emotional support, resilience, and a sense of purpose, which counteract isolation and financial stress [18], highlighting the interplay between financial and social resources in protecting elderly mental health. Therefore, theoretically, economic status and social activities may function as potential moderator in the association between catastrophic health expenditure and mental health in elderly population.

Currently, there’s a scarcity of evidence on the association between CHE and mental health and the potential moderators among the elderly population. Therefore, this study intends to provide a better investigation on the impact of CHE on mental health outcome and the underlying role of financial status and social activity, based on a national representative, longitudinal study in China. We hypothesized that CHE is positively associated with higher levels of depressive symptoms among elderly populations. Furthermore, we proposed that economic conditions and social activity moderate this association, with the association observed to be more pronounced among elderly with lower income or social activity.

Materials and methods

Study population

The data utilized in this research were extracted from the Harmonized China Health and Retirement Longitudinal Study (Harmonized CHARLS). Following a five-stage cluster sampling procedure, the CHARLS is a nationally representative survey that gathers data on demographics, income and spending, health, family structure, health care usage and cost, housing, and employment in Chinese adults over the age of 45. The baseline survey was conducted in 2011, followed by three follow-up surveys in 2013, 2015, and 2018. The four waves of the CHARLS are used to compile the data for this analysis.

Our analysis focused on 15,406 older people older than 60 years of age who had used any health services in the pooled sample after removing cases with missing value of depressive, cost or income information. Figure 1 described the sample selection process.

Measurement

Dependent variable: depressive symptoms

Depressive symptoms were defined as a continuous variable, which is estimated using the Chinese version of the 10-item center for epidemiologic studies depression (CES-D) scale. The scale contains eight negative items (e.g., “I felt everything I did was an effort”) and two-positive items (e.g., “I felt hopeful about the future”). On a four-point scale, each statement was scored as follows: 1 (less than one day), 2 (one to two days), 3 (three to four days), and 4. (five to seven days). Two positive items were marked negatively. The ten items yielded a score between 0 and 30, with a higher score suggesting a greater likelihood of depressive symptoms.

Independent variable: CHE

CHE is the primary independent variable of interest. We established a binary variable that indicated whether the participant incurred catastrophic health expenses. We incorporated two CHE measurements, which was determined by the fraction of a person’s out-of-pocket (OOP) health expenditures relative to the yearly household expenditure per capita. We used a 10%, 20%, and 25% criteria, respectively, to identify CHE cases [19]. Using the Consumer Price Index, the OOP health expenditures were adjusted for inflation and expressed in 2011 prices [20].

Moderator variable

Social activity was measured by respondent’s participation in any social activities. A code of 0 indicates that the respondent didn’t participate in any social groups or social activities, and a code of 1 indicates that the respondent participated in one of the following social activities. Participants were asked, “Have you done any of these activities in the last month,” which was a multiple choice question including 6 activities:1) Interacted with friends; 2) Played Ma-jong, chess, cards, or went to a community club; 3) Went to a sporting event, participated in a social group, or participated in some other sort of club; 4) Took part in a community-related organization; 5) Took part in voluntary or charity work; 6) Attended an educational or training course. Income was defined as categorical variable, which was determined by tertiles of family consumption per capita (high, medium, and low).

Control variables

The control variables were socio-demographic variables, variables of health behavior, physical conditions, and health expenditures. The socio-demographic variables includes age as a continuous variable, gender as a dichotomous variable (male or female), education level as a categorical variable (less than lower secondary, upper secondary & vocational training, or tertiary), residence as a dichotomous variable (urban or rural), marital status as a dichotomous variable (married/cohabiting or separated/divorced/widowed/single), work as a dichotomous variable (employed/involved in work-related activities or not employed), public health insurance as a dichotomous variable (having at least one medical insurance, or none), and number of living children as a continuous variable. Health behaviors include alcohol use as a dichotomous variable (more than once per month or less than once per month) and smoking as a dichotomous variable (current smoker or non-smoker). Physical conditions include activities of daily living (ADL) and instrumental activities of daily living (IADL) as dichotomous variables (were unable to perform or required assistance with a specific job, capable of performing any activities) and chronic disease as a dichotomous variable (yes or no). Health expenditure variable was measured by out-of-pocket health expenditure as a continuous variable (in thousand yuan).

Data analysis

Descriptive results are presented as means and standard deviations (SD) or as numbers and percentages. We employed a mixed-effects linear model to regress CES-D-10 scores against catastrophic health expenditure (CHE), allowing for random intercepts to account for individual-level variation. The association between CHE and CES-D-10 scores was estimated in four stages: (1) Model 1 examined whether CHE incidence is associated with increased levels of depressive symptoms; (2) Model 2 tested whether income moderates the relationship between CHE and depressive symptoms by including an interaction term between CHE and income; (3) Model 3 assessed whether social activities moderate this relationship by adding an interaction term between CHE and social activities; and (4) Model 4 evaluated whether the relationship between CHE and depressive symptoms depends on both income and social activities by incorporating a three-way interaction term (CHE × income × social activities). To ensure the robustness of our findings, we conducted sensitivity analyses using alternative CHE thresholds (20% and 25%) to identify CHE cases. All statistical analyses were conducted using STATA version 16.0 for Mac (Stata Corp, College Station, TX, USA). A two-sided p-value of less than 0.05 was considered statistically significant.

In analytic samples, about 7.3% of respondents have missing data on education, social activity, public health insurance status, drinking, smoking, ADL, or chronic disease. Therefore, we used multiple imputations by chained equations to replace missing values with five imputed values [21].

Ethical approval

The respondents were provided with an informed consent form to read and sign before each interview and each interviewee was offered the option to exit the study at any time. Participation in the survey was voluntary. Ethics approval for the use of CHARLS data was obtained from the University of Newcastle Human Research Ethics Committee (H-2015-0290).

Fig. 1
figure 1

Flowchart of the study sample

Full size image

Results

Sample characteristics

Table 1 presents the descriptive characteristics of the study population. The sample characteristics of participants who had CHE at the threshold level of 10% are compared with those of people who did not experience CHE in Table 1. For the full sample, the mean age was 67.96 years, 49.8% were male, and the mean CES-D score was 9.0. Depression scores were higher among respondents who reported CHE (8.4) in comparison to those with no CHE event (10.2). More than 90% of respondents had less than lower secondary education, 62.0% were from rural area, 50.3% were employed or involved in any work-related activities, and most of the respondents had public health insurance. The mean out-of-pocket health expenditure was higher among the elderly with CHE experience (12.06 thousand yuan) compared to those with no CHE experience (0.10 thousand yuan). The distribution of other sample characteristics including health behaviors and physical conditions were also provided in Table 1.

Table 1 Sample characteristics
Full size table

Association between CHE and depressive symptoms and moderating effect of income and social activity

Table 2 presents the mixed-effects linear model on the association between CHE and depressive symptoms. In Model 1, CHE was significantly associated with CES-D 10 score (coefficient = 0.363, P < 0.05). The association remained significant in Model 2, which includes the interaction term between CHE and income. Comparing with respondents with low income, the association between CHE and depressive symptoms was less pronounced among those from medium or high income group (coefficient=-0.325, P < 0.05). In Model 3, we observed no significant estimate for interaction term between CHE and social activity. In Model 4, which includes the interaction terms of CHE, income groups and social activity, the estimates suggested that in comparison with respondents with low income and having no social activity, the association between CHE and depressive symptoms was less pronounced among respondents with high income and having social activity (coefficient=-1.132, P < 0.05).

Figure 2 presents the adjusted CES-D 10 scores by the incidence of CHE, income groups, and social activity among elderly in China. In Fig. 2a, for lower income group, the adjusted CES-D 10 score was significantly higher among elderly with CHE events in comparison to those without CHE events (difference = 0.77, P < 0.001). However, no significant difference in CES-D 10 score between elderly with CHE and those without CHE for medium and higher income groups. In Fig. 2b, for elderly having no social activity, the adjusted CES-D 10 score was significantly higher among elderly with CHE events in comparison to those without CHE events(difference = 0.37, P = 0.034), no significant difference between elderly with CHE and those without CHE for those having social activity. Figure 2c and d showed the difference of CES-D 10 score between elderly with and without CHE event by different income groups and social activity. Among elderly having no social activity, we observed a 0.93-point higher CES-D 10 score in elderly with a CHE event in comparison to those without CHE event (P < 0.001). However, among elderly with social activity, no significant difference was observed between those with and without a CHE event in all income groups.

Table 2 Adjusted association between CHE and depressive symptoms, and the moderating effect of social activity and income
Full size table
Fig. 2
figure 2

Adjusted1 CES-D 10 scores by the incidence of CHE, income groups, and social activity among elders in China

1Adjusted for age, gender, education level, residence, marital status, work, public health insurance, number of living children, alcohol use, smoking, activities of daily living (ADL), instrumental activities of daily living (IADL), chronic disease and out-of-pocket health expenditure

Full size image

Robustness check

Table 3 reports the results of the robustness checks. We further adjusted the thresholds to 20% and 25%, regardless of the criterion, the pattern of the association between CHE and CES-D 10 score, as well as the pattern of interaction terms, was similar to that for the threshold of 10%. CHE was significantly associated with CES-D 10 score, indicating that elderly individuals who did not have CHE tended to have better mental health than those who did. The pattern for the moderating effect of income and social activity was similar to that in our main results.

Table 3 Robustness checks
Full size table

Discussion

This study examined the association between CHE event and depressive symptoms in elderly population, based on a nationwide, longitudinal survey in mainland China. Overall, we found that the incidence of CHE was positively associated with the development of depressive symptoms, and such an association was more pronounced among elderly from the low-income group or without any engagement in social activity. And especially for those who are both socially inactive and poor, the risk of developing depressive symptoms from a CHE event was highest. The detailed discussion of our findings is illustrated below.

First, the results of our research indicate that CHE experience is significantly linked to developing depressive symptoms. These findings are in line with the findings of a large body of research that has uncovered a clear connection between economic pressures and mental health [22,23,24]. It is not generally acknowledged that depression is related with CHE and poverty; yet, the degree of economic income plays an essential role in this process. OOP payments have been shown to be sources of both catastrophic spending and destitution, and there is substantial evidence to support this [25]. Additionally, the psychological burden of CHE, such as chronic stress and feelings of helplessness, may exacerbate depressive symptoms, particularly among elderly populations with limited financial resilience. Addressing these challenges requires targeted interventions that reduce financial barriers to healthcare access while simultaneously addressing the mental health needs of vulnerable groups.

Second, the association between CHE and depressive symptoms was shown to be less pronounced among individuals who participated in social activities. As mentioned before, social activity moderates the relationship between CHE and depressive symptoms by providing emotional support, reducing isolation, and enhancing coping mechanisms, according to activity theory and supported by empirical evidence [18]. Participating in social activities that provide consistent emotional support can have a positive impact on an individual’s mental health over the course of their lifetime. It has been demonstrated that engaging in social activities leads to an increase in one’s sense of well-being [26, 27] and quality of life [28], the formation of social relationships, and a reduction in feelings of loneliness and sadness [29]. Because participating in social activities helps one to make more friends and exchange positive or bad feelings, individuals can acquire self-efficiency, self-esteem, and experience better mental health, which in turn reduces their depressive symptoms [30]. Engaging in social activities fosters resilience, mitigates stress-related physiological responses, and offers practical assistance, thereby buffering the psychological impact of financial strain [18]. It may be beneficial to encourage people to participate in more social activities for better mental health, given the strong correlation between social interactions and lower levels of depression. A meta-analysis of randomized controlled studies found that exercise is as effective as medication and psychotherapy for reducing depressed symptoms [31]. As time passes, social activities continue to be a source of emotional support outside of the family, indicating that regardless of changes in time or location, boosting social involvement may be an effective intervention for relieving depression symptoms. For example, more opportunities for people to get out and mingle could be provided through community/village or social organizations.

Third, the association between CHE and depressive symptoms is more pronounced among elderly individuals with low income. This was consistent with previous studies on similar topics [32,33,34,35]. This finding shows that raising one’s financial income can help to alleviate the mental health burden caused by CHE events. Substantial monetary assistance must be accompanied by a concentrated effort toward achieving social equity. As in many other nations, the impoverished in China have larger care demands than the wealthy and are hence more prone to experience CHE. It is crucial that the present Social Health Insurance (SHI) system offers adequate benefits to the poorest part of the elderly population and protects them from financial difficulty caused by CHE. China has continued to enhance its support for vulnerable rural people. The rural population living in poverty declined from 10.2% in 2012 to 1.7% in 2018, and absolute poverty was eradicated by the end of 2020 [36]. Stronger financial protection measures are required since a nontrivial number of households have faced catastrophic expenditures when attempting to acquire healthcare services [37]. Consequently, policymakers should strengthen existing welfare systems, and programs for low-income communities should prioritize investments in medicine and other health-enhancing technologies in order to eradicate health disparities.

This study highlights the pressing need for policy reforms to address the dual burden of catastrophic health expenditure (CHE) and mental health issues among China’s elderly population. Despite significant progress through social health insurance schemes such as the Urban Employee Basic Medical Insurance (UEBMI) and the New Rural Cooperative Medical Scheme (NCMS), critical gaps persist in mental health service provision. Mental health services remain underfunded, poorly integrated into primary care, and inaccessible to rural and low-income elderly populations, exacerbating vulnerabilities to both financial hardship and depression [38]. Addressing these challenges requires integrating mental health screening and counseling into primary care under the Healthy China 2030 initiative, which could bridge the treatment gap, particularly for chronic disease patients at high risk of CHE [39]. Training community health workers in psychological first aid and expanding insurance coverage for psychotherapy and antidepressants would further enhance accessibility. Strengthening public-private partnerships to subsidize low-income elderly through programs like Critical Illness Insurance could alleviate financial strain while improving mental health outcomes [39]. Additionally, community-based anti-stigma campaigns and mental health education initiatives could reduce barriers to care and encourage early intervention [40]. These reforms would leverage China’s existing healthcare infrastructure to address systemic inequities and promote holistic well-being among the elderly.

Attention must be paid to the limitations of this study. First, our research did not account for the possibility that CHE has a lingering effect on one’s mental health over time. Second, because indirect costs of health care, such as transportation and housing, were not factored into the total cost of health care, it is possible that the incidence of CHE was underreported. Third, poor households are more likely to report zero health spending due to unaffordability than other non-poor households, which may also lead to potential bias of our analysis. Another limitation is the potential for unmeasured confounders (e.g., health-seeking behavior). Nevertheless, our sensitivity analyses showed stable effect sizes, suggesting residual confounding is unlikely to fully explain the findings.

Conclusions

This study suggested a positive association between CHE events and depressive symptoms among elderly in China, as well as the protective effect of high financial status and engagement of social activity in such association. Given the context of rapid global population aging, our research underlines the urgent need for action by government and public health authorities, such as the integration of mental health services for the national health system, the financial subsidies, and the promotion of community support organization strategies to address the high expenditure, psychological stress among the elderly, especially for low-income households or those living alone.

Data availability

The datasets generated analysed during the current study are available at http://charls.pku.edu.cn.

Abbreviations

CHE:

Catastrophic Health Expenditure

CHARLS:

China Health and Retirement Longitudinal Study

References

  1. Patel V, et al. Addressing the burden of mental, neurological, and substance use disorders: key messages from disease control priorities. Lancet. 2016;387(10028):1672–85.

    PubMed  Google Scholar 

  2. Zhou L, Ma X, Wang W. Relationship between cognitive performance and depressive symptoms in Chinese older adults: the China health and retirement longitudinal study (CHARLS). J Affect Disord. 2021;281:454–8.

    PubMed  Google Scholar 

  3. Zhou P, et al. Association between chronic diseases and depression in the middle-aged and older adult Chinese population—a seven-year follow-up study based on CHARLS. Front Public Health. 2023;11:1176669.

    PubMed  PubMed Central  Google Scholar 

  4. Liu X, et al. The mediation role of sleep quality in the relationship between cognitive decline and depression. BMC Geriatr. 2022;22(1):178.

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Sui M, et al. Catastrophic health expenditures of households living with pediatric leukemia in China. Cancer Med. 2020;9(18):6802–12.

    PubMed  PubMed Central  Google Scholar 

  6. Hogan DR, et al. Monitoring universal health coverage within the sustainable development goals: development and baseline data for an index of essential health services. Lancet Global Health. 2018;6(2):e152–68.

    PubMed  Google Scholar 

  7. Yip W, et al. 10 years of health-care reform in China: progress and gaps in universal health coverage. Lancet. 2019;394(10204):1192–204.

    PubMed  Google Scholar 

  8. Barasa EW, Maina T, Ravishankar N. Assessing the impoverishing effects, and factors associated with the incidence of catastrophic health care payments in Kenya. Int J Equity Health. 2017;16:1–14.

    Google Scholar 

  9. Wagstaff A, et al. Progress on catastrophic health spending in 133 countries: a retrospective observational study. Lancet Global Health. 2018;6(2):e169–79.

    PubMed  Google Scholar 

  10. Allen J, et al. Social determinants of mental health. Int Rev Psychiatry. 2014;26(4):392–407.

    PubMed  Google Scholar 

  11. Amroussia N, Gustafsson PE, Mosquera PA. Explaining mental health inequalities in Northern Sweden: a decomposition analysis. Global Health Action. 2017;10(1):1305814.

    PubMed  PubMed Central  Google Scholar 

  12. Kelley-Moore JA, et al. Do local social hierarchies matter for mental health? A study of neighborhood social status and depressive symptoms in older adults. Journals Gerontol Ser B: Psychol Sci Social Sci. 2016;71(2):369–77.

    Google Scholar 

  13. Aregbeshola BS, Khan SM. Determinants of catastrophic health expenditure in Nigeria. Eur J Health Econ. 2018;19:521–32.

    PubMed  Google Scholar 

  14. Yang W, Hu B. Catastrophic health expenditure and mental health in the older Chinese population: the moderating role of social health insurance. Journals Gerontology: Ser B. 2022;77(1):160–9.

    Google Scholar 

  15. Li J, et al. Catastrophic health expenditure and health-related quality of life among older adults in Shandong, China: the moderation effect of daily care by adult children. Int J Equity Health. 2024;23(1):51.

    PubMed  PubMed Central  Google Scholar 

  16. Domènech-Abella J, et al. Loneliness and depression in the elderly: the role of social network. Soc Psychiatry Psychiatr Epidemiol. 2017;52:381–90.

    PubMed  Google Scholar 

  17. Muramatsu N, Yin H, Hedeker D. Functional declines, social support, and mental health in the elderly: does living in a state supportive of home and community-based services make a difference? Soc Sci Med. 2010;70(7):1050–8.

  18. Adams KB, Leibbrandt S, Moon H. A critical review of the literature on social and leisure activity and wellbeing in later life. Ageing Soc. 2011;31(4):683–712.

    Google Scholar 

  19. Wagstaff A, et al. Progress on catastrophic health spending in 133 countries: a retrospective observational study. Lancet Glob Health. 2018;6(2):e169–79.

    PubMed  Google Scholar 

  20. Statistics. CNBo. Consumer price index. Editor: C.N.B.o. Statistics.; 2020.

    Google Scholar 

  21. Royston P. Multiple imputation of missing values: update of ice. STATA J. 2005;5:527–36.

    Google Scholar 

  22. Yang W, Hu B. Catastrophic health expenditure and mental health in the older Chinese population: the moderating role of social health insurance. J Gerontol B Psychol Sci Soc Sci. 2022;77(1):160–9.

    PubMed  Google Scholar 

  23. Hiilamo A, Grundy E. Household debt and depressive symptoms among older adults in three continental European countries. Aging Soc. 2020;40(2):412–38.

    Google Scholar 

  24. Zhao L, et al. Depressive symptoms and ADL/IADL disabilities among older adults from low-income families in Dalian, Liaoning. Clin Interv Aging. 2022;17:733–43.

    PubMed  PubMed Central  Google Scholar 

  25. Whitehead M, Dahlgren G, Evans T. Equity and health sector reforms: can low-income countries escape the medical poverty trap? Lancet. 2001;358(9284):833–6.

    CAS  PubMed  Google Scholar 

  26. Liu J et al. Social engagement and elderly health in China: evidence from the China health and retirement longitudinal survey (CHARLS). Int J Environ Res Public Health. 2019;16(2).

  27. Shi X, et al. Happiness, depression, physical activity and cognition among the middle and old-aged population in China: a conditional process analysis. PeerJ. 2022;10:e13673.

    PubMed  PubMed Central  Google Scholar 

  28. Goh HT, et al. Social participation determines quality of life among urban-dwelling older adults with stroke in a developing country. J Geriatr Phys Ther. 2019;42(4):E77–84.

    PubMed  Google Scholar 

  29. Gale CR, Westbury L, Cooper C. Social isolation and loneliness as risk factors for the progression of frailty: the english longitudinal study of ageing. Age Ageing. 2018;47(3):392–7.

    PubMed  Google Scholar 

  30. Mumba MN, et al. Intensity and type of physical activity predicts depression in older adults. Aging Ment Health. 2021;25(4):664–71.

    PubMed  Google Scholar 

  31. Kvam S, et al. Exercise as a treatment for depression: a meta-analysis. J Affect Disord. 2016;202:67–86.

    PubMed  Google Scholar 

  32. Yu X, Liu S. Stressful life events and Chinese older people depression: moderating role of social support. Front Public Health. 2021;9:768723.

    PubMed  PubMed Central  Google Scholar 

  33. Lau YW, et al. Social support network typologies and their association with dementia and depression among older adults in Singapore: a cross-sectional analysis. BMJ Open. 2019;9(5):e025303.

    PubMed  PubMed Central  Google Scholar 

  34. Chan E, et al. Associations among living alone, social support and social activity in older adults. AIMS Public Health. 2020;7(3):521–34.

    PubMed  PubMed Central  Google Scholar 

  35. Sánchez-Moreno E, Gallardo-Peralta LP. Income inequalities, social support and depressive symptoms among older adults in Europe: a multilevel cross-sectional study. Eur J Ageing. 2022;19(3):663–75.

    PubMed  Google Scholar 

  36. Le-rong YU. The effects of social security expenditure on reducing income inequality and rural poverty in China. J Integr Agric. 2021;20(4):1060–7.

    Google Scholar 

  37. Eze P, et al. Catastrophic health expenditure in sub-Saharan Africa: systematic review and meta-analysis. Bull World Health Organ. 2022;100(5):337–j351.

    PubMed  PubMed Central  Google Scholar 

  38. Sun J, Lyu S. The effect of medical insurance on catastrophic health expenditure: evidence from China. Cost Eff Resource Allocation. 2020;18:1–11.

    Google Scholar 

  39. Yip W, Hsiao W. Harnessing the privatisation of China’s fragmented health-care delivery. Lancet. 2014;384(9945):805–18.

    PubMed  PubMed Central  Google Scholar 

  40. Xiang YT, et al. Rethinking progress and challenges of mental health care in China. World Psychiatry. 2018;17(2):231.

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

N/A.

Funding

N/A.

Author information

Authors and Affiliations

  1. Peking University Sixth Hospital, Peking University Institute of Mental Health, National Health Commission Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Huayuanbeilu No.51, Beijing, 100191, China

    Siwei Sun, Xuechun Wang & Ruoxi Ding

  2. China Population and Development Research Center, Beijing, China

    Na Guo

  3. Shandong Institute of Brain Science and Brain-inspired Research, Medical Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, China

    Peipei Li

  4. Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing, 100191, China

    Dawei Zhu

  5. International Research Center for Medicinal Administration (IRCMA), Peking University, Beijing, 100191, China

    Dawei Zhu

Authors
  1. Siwei Sun
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Xuechun Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Na Guo
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Peipei Li
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Ruoxi Ding
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Dawei Zhu
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

SS, RD and DZ planned the study, led the conceptualization of the study and the analysis of the data, and wrote and revised the manuscript. XW, NG and PL contributed to the conceptualization of the study, conducted supplementary data analysis, and revised the manuscript.

Corresponding authors

Correspondence to Ruoxi Ding or Dawei Zhu.

Ethics declarations

Ethics approval and consent to participate

The data used in this study were retrieved from the CHARLS. This survey was endorsed by the Biomedical Ethics Committee of Peking University (NO.IRB 00001052–11015). All participants in the survey signed or marked (if illiterate) the informed consent forms. All procedures were in accordance with the ethical standards of the Helsinki Declaration. Participants provided informed consent before data collection.

Consent for publication

N/A.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, S., Wang, X., Guo, N. et al. Association between catastrophic health expenditure and mental health among elderly in China: the potential role of income and social activity. BMC Geriatr 25, 231 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-05887-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-025-05887-9

Keywords

BMC Geriatrics

ISSN: 1471-2318

Contact us