Chronic Diseases and Catastrophic Health Expenditures in Elderly Chinese Households: A Cohort Study

doi:10.21203/rs.3.rs-4903883/v1

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Research Article

Chronic Diseases and Catastrophic Health Expenditures in Elderly Chinese Households: A Cohort Study

https://doi.org/10.21203/rs.3.rs-4903883/v1

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Background

In light of China's demographic transition towards an increasingly aged population coupled with a high prevalence of chronic conditions, there has been a pronounced augmentation of economic pressures on elderly households as well as on the national healthcare system. This research explores the determinants of catastrophic health expenditure (CHE) among Chinese households that include elderly individuals diagnosed with chronic diseases.

Methods

Utilizing data from the 2011 China Health and Retirement Longitudinal Study (CHARLS), conducted by the National School of Development at Peking University, this research focuses on households with at least one member aged 60 or older diagnosed with a chronic disease. CHE is measured by the proportion of out-of-pocket health payments in relation to total household expenditures, excluding food. The study constructed panel data from the follow-up surveys in 2015, 2018, and 2020, and used logistic regression to analyze the impact of various factors on CHE, including the presence of chronic diseases, age, education level, marital status, household registration (hukou), place of residence, and basic medical insurance coverage.

Result

The analysis indicates that chronic diseases significantly increase the likelihood of incurring CHE in elderly households, even if there is only one chronic illness. Key factors affecting CHE include age, education level, marital status, hukou, and residence. Notably, basic medical insurance did not significantly reduce the risk of CHE. Statistical data show that households with chronic diseases have a higher tendency toward CHE (P < 0.001, 95% CI: 1.36–1.64).

Conclusion

Chronic diseases have emerged as a dominant risk factor for catastrophic health expenditures (CHE) among elderly households in China, yet basic medical insurance has not adequately mitigated these expenditures.The findings highlight the urgent need for policy interventions to strengthen financial protections and enhance social health insurance schemes, thereby reducing the financial vulnerability of elderly households facing health shocks.

chronic disease1

catastrophic health expenditures2

elderly household3

health insurance4

China5

Each year, 44 million households worldwide encounter catastrophic health expenditures (CHE), especially in low and middle-income countries with inadequate healthcare systems[1]. CHE occurs when a family's healthcare costs surpass a significant portion of their income, which will severely affect their well-being, increase the risk of poverty, and thereby widen the gap between the wealthy and vulnerable groups[2]. In China, the prevalence of such financially ruinous health costs is on the rise among households.

In recent years, chronic diseases have become a significant public health problem impacting China’s economic and social development. Meanwhile, chronic conditions are major contributors to the health burden, health outcome inequalities, and economic strain. Research data indicates that the proportion of deaths caused by chronic diseases in China increased from 80.0% in 2002 to 86.6% in 2012 and 88.5% in 2018[3]. If no effective measures are taken to curb this, then rapid ageing may increase the economic burden of chronic diseases by 40% by 2030[4]. Furthermore, the burden of chronic diseases is not only heavy for countries, but also for individuals and households. For example, Evidence from Iran consistently shows that households with members suffering from chronic illnesses are more likely to experience economic hardships and are at a heightened risk of falling into poverty compared to other families[5]. In Greece, the incidence of CHE among households with chronically ill members is significantly higher than in others[6]. Further, several studies in China have observed that households with chronic conditions bear greater financial risks than others, especially in sub-poverty level families[7].

Despite extensive studies focus on catastrophic health expenditures (CHE) among older adults with chronic disease patients and the association between multimorbidity and CHE, there are still several gaps remain. Existing studies have predominantly focused on the financial burden of specific severe diseases, such as cancer[8–11]. Other studies also emphasized the impact of multimorbidity on CHE[12–14]. Few studies have analysed the association between chronic diseases incidence and CHE, and there is a lack of exploration into the differences in the impact of single and multiple chronic diseases on CHE. In addition, most existing studies are cross-sectional, lacking longitudinal research to enhance the explanatory power.

Therefore, this study aims to use a nationally representative dataset from 2013 to 2020 to explore the association between chronic disease and CHE among elderly in China, and analyse the risks of poverty due to single chronic diseases and multimorbidity. This study will be benefit to fill the literature gap and provide the latest evidence for CHE related research.

Data sources

This study utilizes longitudinal data from the China Health and Retirement Longitudinal Study (CHARLS), which is coordinated by the National Development Research Institute at Peking University. CHARLS aims to collect comprehensive data across multiple waves to assess various aspects of the aging population in China. This includes demographic information, family composition, employment and retirement status, income and expenditure levels, as well as detailed health metrics such as general health status, insurance coverage, and the utilization of health services.

For the purpose of this analysis, the study examined data from four survey waves—2013, 2015, 2018, and 2020. The initial 2013 survey serves as the baseline for this study, with data from 2015, 2018, and 2020 used to construct a balanced panel dataset. The baseline survey was conducted between June 2011 and March 2012, targeting household members aged 45 and older. Spouses of the primary respondents were automatically included, leading to a comprehensive initial sample of 18,605 participants.

From this initial cohort, the study applied specific inclusion and exclusion criteria to refine the sample for longitudinal tracking. Households were excluded if they did not include any members aged 60 years or older or lacked crucial data points.To further focus on the financial impact of health issues, the analysis only included households that did not report catastrophic health expenditures in 2013. These selected households were then followed biennially, culminating in a final sample of 6,050 participants by the 2020 wave for the current analysis. Figure 1 illustrates the sample selection process across the different survey waves, detailing both the attrition and inclusion at each stage.

Dependent variable

Catastrophic Health Expenditure (CHE) is a critical metric used to evaluate the financial impact of out-of-pocket health care expenditures on household finances. CHE occurs when these expenditures exceed a predefined threshold, representing a significant financial burden on households. Generally, CHE is operationalized using two widely recognized thresholds to determine whether health expenditures can be considered catastrophic:

(1)10% of Total Household Expenditure: This threshold considers out-of-pocket healthcare payments that exceed 10% of a household's total annual expenditure[15, 16]. This includes all household spending, encompassing daily living costs, utilities, transportation, and other non-discretionary spending.

(2)40% of Non-Food Expenditure: This threshold evaluates whether out-of-pocket healthcare payments constitute more than 40% of the household's total non-food expenditure[17]. Non-food expenditure is often used as a proxy for discretionary spending and is considered a more accurate reflection of a household’s financial capacity to absorb health-related costs

Data Quality and Socioeconomic Status Measurement: In many low- and middle-income countries, income data are often unreliable or incomplete. Therefore, consumption expenditure is frequently utilized as an alternative measure of socioeconomic status due to its generally more accurate reporting. The broader scope of consumption data includes but is not limited to household expenses on utilities, communication, transportation, domestic services, entertainment, personal care, and education.

Operational Definition in Current Study: For the purposes of this analysis, only the health expenditures incurred by the respondent and their spouse are considered. These expenses encompass costs associated with outpatient visits, hospital admissions, and medications incurred over the past year.

Calculation of Non-Food Expenditure (CTP): In this study, Total Non-Food Expenditure (CTP) is calculated by deducting essential subsistence needs (i.e., food) from total household expenditure. This measure includes expenditures on communication, utilities, fuel, local transportation, domestic help, entertainment, daily necessities, dining out, education, out-of-pocket health expenses (excluding portions covered by insurance such as Medicare), personal fitness and beauty, rent, maintenance, taxes, donations, and household durable goods.

If a surveyed household's annual health spending crosses these thresholds, the dependent variable is coded as 1, indicating the presence of catastrophic health expenditures. If it does not, it is coded as 0, indicating absence.

Independent variable

The primary independent variable in this study is chronic disease status, defined using a binary metric based on the presence or absence of chronic diseases among participants. This operationalization draws on data collected through the China Health and Retirement Longitudinal Study (CHARLS), which systematically captures health information across a nationally representative aging population.

Chronic Conditions Assessed: In CHARLS, participants were asked to report if they had been diagnosed with any of the following 14 chronic conditions by a healthcare professional: including hypertension, dyslipidemia, diabetes, cancer or malignant tumor, chronic lung diseases, liver diseases, heart attack, stroke, kidney diseases, stomach and other digestive diseases, emotional, nervous and psychiatric problems, memory-related diseases, arthritis and rheumatism, and asthma.

Coding of Variable: For analytical purposes, the chronic disease variable is coded dichotomously. A value of 1 is assigned to respondents who report having one or more of the listed chronic conditions, indicating the presence of chronic disease. Conversely, a value of 0 is assigned to those with no reported chronic conditions, indicating the absence of chronic disease.

Justification for Use as an Independent Variable: The inclusion of chronic disease status as an independent variable is predicated on the substantial body of evidence linking chronic health conditions with both increased healthcare utilization and heightened financial vulnerability. Chronic diseases often require long-term management and treatment, which can lead to significant out-of-pocket healthcare expenditures and potentially catastrophic financial impacts on households.

Analytical Considerations: The binary nature of this variable allows for clear distinction in the analysis of health expenditure patterns between individuals with and without chronic conditions, thus facilitating a more nuanced understanding of the financial burden of health care among aging populations in China.

Household and respondent characteristic

This study systematically categorizes household and respondent characteristics to elucidate their potential impact on health expenditures.

Household Characteristics: Place of Residence: Categorized as urban or rural, this variable reflects the geographical diversity of the sample. Marital Status: Defined as living with a spouse for those who are married or cohabiting, and not living with a spouse for those who are unmarried, separated, divorced, or widowed. This variable reflects the family support structure of the sample.

Respondent Characteristics: Demographic Information: Includes gender (male, female) and age (in years), providing a demographic profile of the cohort.Educational Attainment: Classified into three categories—elementary school and below, junior high school, and high school and above. This categorization helps assess the correlation between education level and health outcomes or expenditures.

Health-related Variables: Consist of the prevalence of chronic diseases (yes, no) and health insurance coverage (yes, no). Insurance coverage is further subdivided into three major types of basic medical insurance programs in China: basic medical insurance for urban employees, basic medical insurance for urban residents, and the new rural cooperative medical scheme. These variables are crucial for evaluating the burden of healthcare costs.

Statistical analysis

Initial analysis employed descriptive statistics to outline the baseline characteristics of the study population. This included computing means and standard deviations for continuous variables, and frequencies and percentages for categorical variables.

The core of our analytical framework is a binary logistic regression model, which was utilized to explore the potential predictors of catastrophic health expenditures (CHE). CHE was defined using the threshold of non-food expenditures exceeding 40% of total household expenditures. This threshold is particularly relevant for low-income households as it mitigates the bias introduced by essential food expenditures.

We conducted stratified analyses to assess how chronic diseases influence catastrophic health expenditures (CHE) across different demographic segments, including varying genders and chronic disease statuses. This approach allows for a deeper understanding of the factors influencing CHE in different subpopulations and helps analyze the impact of single chronic diseases and multimorbidity on household economic conditions.

Sensitivity analyses were performed using alternative definitions of CHE to validate the robustness of our findings. This step is crucial to ensure that our results are not overly dependent on the chosen threshold.

Data from the CHARLS questionnaire were processed and cleaned using R programming language, ensuring accurate and efficient handling of the dataset. The statistical analyses were performed using Stata17. A two-sided p-value of less than 0.05 was considered statistically significant for all tests.

Socio-demographic and household characteristics of the participants

This section presents an overview of the demographic and socio-economic characteristics of the study population across three waves of the China Health and Retirement Longitudinal Study (CHARLS) collected in 2015, 2018, and 2020. The average age of the participants is 70.52 years, reflecting the aging cohort under study.

The proportion of participants residing in urban and rural areas is quite similar, with a slightly higher percentage in rural areas(58%). This distribution reflects China's population demographics and the outcomes of urbanization.The gender distribution was slightly skewed towards females, who constituted 52.0% of the sample.The majority of participants have a low level of education, with the primary concentration being at the primary school level or below.This educational distribution is critical as it correlates with other socioeconomic factors such as employment in agriculture and living conditions.

Most households had a strong familial support structure, as evidenced by 62% of household members living with a spouse, which may influence health outcomes and care-seeking behaviours.

Reflecting socio-economic conditions, a large portion of respondents had agricultural household registrations, a status that has implications for their access to health services and insurance schemes. The prevalence of agricultural registrations and rural residence suggests a demographic profile that may face specific challenges in accessing healthcare and financial resources. The basic medical insurance coverage rate has reached 99%, achieving near-universal coverage.

Detailed statistics are presented in Table 1, which includes the distribution of age, gender, education level, marital status, household registration, place of residence, and basic medical insurance coverage. This table provides a concise overview of the cohort's characteristics, facilitating subsequent data analysis.

Table 1

Descriptive Statistics for Study Variables (N = 6050)
Variables	Definition	Mean (SD)
CHE	0 = NO 1 = YES	0.15 (0.36)
Chronic Disease	0 = NO 1 = YES	0.49 (0.50)
Age	Age in years	70.52 (6.91)
Gender	0 = Female 1 = Male	0.48 (0.50)
Education	0 = Primary or Below 1 = Middle School level 2 = Secondary or Higher	0.30 (0.64)
Marriage	0 = No spouse 1 = With spouse	0.38 (0.79)
Hukou type	0 = Urban 1 = Rural	0.25 (0.43)
Area	0 = Urban 1 = Rural	0.42 (0.49)
Insurance or not	0 = Not insured 1 = Insured	0.99 (0.12)
^a Abbreviations. CHE = Catastrophic Health Expenditure; SD = Standard Deviation

Determinants of catastrophic health expenditure

Our analysis identified several key factors that influence the likelihood of households incurring catastrophic health expenditures (CHE). In regression analysis, the presence of chronic diseases (p < 0.001), age (p < 0.01), education level (p < 0.001), marital status (p < 0.001), hukou (p < 0.001), and residence (p < 0.001) were significantly associated with CHE. Chronic diseases increase the risk of incurring CHE. Additionally, the older the age, the higher the risk of CHE. Higher education levels reduce the occurrence of CHE. Living with a spouse reduces the occurrence of CHE, reflecting the potential financial protective effect of marital status.

Notably, compared to elderly households in rural areas, those in urban areas are more likely to incur CHE. This may be because urban households generally have better economic conditions and are more likely to seek medical treatment when ill, rather than letting the illness progress. Urban areas also have better accessibility to medical services, making it more convenient for residents to seek medical care. However, the existing basic medical insurance system is insufficient to alleviate the risk of households incurring CHE. Our data analysis results indicate that medical insurance does not have a significant impact on CHE, corroborating this point. These findings highlight the substantial financial burden that chronic health conditions and other adverse conditions can impose on households. Detailed statistical outputs are presented in Table 2, which illustrates the influence of each variable on the likelihood of CHE occurring within the cohort.

Table 2

Analysis of the impact of chronic diseases on catastrophic health expenditures(N = 6050)
Variables		Odds Ratio (95%CI)
Chronic disease (compared with no chronic disease)
Chronic disease		1.49^*** (1.36–1.64)
Age		1.01^** (1.00-1.02)
Gender (compare with female)
Male	1.01 (0.92–1.13)
Education (compare with Primary or Below)
Middle School level and higher	0.75^*** (0.68–0.82)
Married (compare with no spouse)
Living with spouse	0.87^*** (0.82–0.93)
Hukou (compared with urban)
Rural	0.65^*** (0.57–0.75)
Residence (compared with urban)
Rural	0.77^*** (0.70–0.85)
Insurance status (compared with no insurance)
Insurance	1.43 (0.72–2.86)
p < 0.05, p < 0.01, **p < 0.001; 0R, odds ratio.

To ensure the robustness of our findings, sensitivity analyses were conducted using different thresholds for defining CHE. These thresholds were set at ≥ 25% of the total non-food household expenditure, and ≥ 10% and ≥ 25% of the total household expenditure. The consistency of results across these varying thresholds confirms the reliability of our main findings and suggests that our conclusions about the determinants of CHE are stable regardless of the specific threshold applied. The outcomes of these sensitivity analyses are documented comprehensively in Tables 3, providing a transparent view of how varying definitions of CHE affect the analysis.

Table 3

Association between chronic disease and catastrophic health expenditure with different thresholds. (N = 6050)
Variables	Catastrophic health expenditure with different thresholds,
Variables	Threshold1	Threshold2
Chronic disease	1.55^*** (1.44–1.68)	1.59^*** (1.48–1.71)
Control variables	Control	Control
N	6050	6050
^aThreshold 1:≥25% of households' total expenditure; Threshold 2: ≥10% of households' total non-food expenditure
^bp < 0.05, p < 0.01, **p < 0.001.

Results of the Stratification Analyses

Stratification analyses were employed to delve the effects of chronic disease prevalence on CHE across different demographic subgroups. These analyses revealed nuanced differences in how chronic diseases impact health spending catastrophically.Results indicate that regardless of whether the participants are male or female, having a chronic disease significantly impacts the occurrence of catastrophic health expenditures (CHE).

Moreover, we further analyzed the impact of the number of chronic diseases on catastrophic health expenditures (CHE). The results revealed that having either a single chronic disease or multiple chronic diseases significantly affects CHE. This indicates that even the presence of a single chronic disease in elderly households significantly increases the risk of incurring CHE, highlighting the importance of addressing the economic impact of individual chronic diseases on households.

The detailed findings from these stratified analyses are illustrated in Tables 4 and 5, which provide a breakdown of the impact by demographic subgroup.

Table 4

Association between chronic disease and catastrophic health expenditure with different gender
Variables	Male	Female
Chronic disease	1.61^*** (1.45–1.78)	1.45^*** (1.27–1.65)
Control variables	Control	Control
N	2791	3259
p < 0.05, p < 0.01, **p < 0.001

Table 5

Association between chronic disease and catastrophic health expenditure with different thresholds with different chronic disease conditions
Variables	number of chronic diseases = 1	number of chronic diseases ≥ 2
Chronic disease	1.39^*** (1.23–1.56)	1.27^*** (1.19–1.35)
Control variables	Control		Control
N	5249		5955
p < 0.05, p < 0.01, **p < 0.001

This study underscores a significant burden of catastrophic health expenditures (CHE) among elderly households in China. Approximately 15% of older households were spending more than 40% of their non-food expenditures on health, categorizing these outlays as catastrophic. Notably, the prevalence and intensity of CHE are markedly higher in households with chronic disease sufferers compared to those without, highlighting the profound impact of chronic conditions on financial health vulnerability. Previous studies have indicated that comorbidities of chronic diseases are significant determinants of catastrophic health expenditures[12, 14, 18–20]. Additionally, some research has focused on more severe illnesses such as cancer, stroke, and heart disease, identifying these serious conditions, which can be termed as "health shocks," as important contributors to catastrophic health spending[11–15]. Nevertheless,our study revealed that if any family member suffers from any chronic illness, even if it is not one of the aforementioned severe diseases, it will impact the household's economic situation, increasing the risk of falling into poverty. Whether it is a single chronic illness or multiple comorbidities, the risk of catastrophic health expenditures significantly increases, having a notable impact on the household's financial condition.

Chronic diseases significantly increase the probability of incurring catastrophic health expenditures (CHE), highlighting the need for targeted health policies. Various countries have implemented specific measures to reduce the impact of diseases on CHE. For example, Turkey's health transformation project reduced the proportion of households with catastrophic expenditures from 0.81% in 2002 to 0.17% in 2011, demonstrating that effective health policies can significantly reduce the occurrence of CHE[14]. However, studies have also shown that South Korea's National Health Insurance expansion policy had no average effect on reducing household impoverishment or unmet needs[21], and despite Iran's implementation of a health transformation plan, a high proportion of households still face CHE[22, 23]. Our study further suggests that these policies should prioritize elderly individuals with chronic conditions, aiming to alleviate the economic burden these diseases impose on households.

Our study also reveals that marital status is a key determinant of catastrophic health expenditures. Households without cohabiting spouses face a higher risk of catastrophic health expenditures, indicating that family support plays a significant role in financial vulnerability to healthcare costs, as mentioned in other studies as well[12].

The study also indicates that China's rural and urban resident medical insurance, urban employee medical insurance, and urban resident medical insurance have not significantly reduced the risk of catastrophic health expenditure (CHE). This is consistent with some research findings regarding the impact of another type of insurance within China's social medical insurance system on catastrophic health spending[13–16],Other research results also suggest that post-reform, medical insurance in China still fails to decrease the incidence of catastrophic health expenditure[24–29].This ineffectiveness suggests that they are not doing enough to shield elderly households from the economic pressure brought on by chronic diseases. This could be attributed to the high prevalence of chronic diseases among the elderly population and current limitations in policy design and implementation.

Research analysis shows that suffering from chronic diseases, even if it is only one chronic disease, seriously affects the medical expenditure, consumption level, and living conditions of Chinese elderly families. Therefore, More targeted measures should be taken to reduce the occurrence of catastrophic health expenditure of elderly households. Social health insurance schemes, organized and sponsored by the government, are designed to protect their members from catastrophic health expenditures, but according to our findings, this goal is virtually unattainable among vulnerable groups. This may be due to high medical costs, low levels of effective reimbursement and limited coverage10.In response to the above problems, the study puts forward the following suggestions: First, relax the reimbursement coverage and compensation ceiling of chronic disease insurance, and adjust the scope of "reasonable compliance costs" in time according to the changes of diseases, so as to provide more medical subsidies for seriously ill families. Second, in order to ensure fairness, a reasonable starting line should be set according to different incomes, so as to reduce the medical burden of elderly families and reduce the catastrophic medical expenses that may occur. Third, optimize the allocation of medical resources, improve the level of primary medical services, reduce the cost of medical treatment for residents, and mitigate the impact of difficult and expensive medical treatment.

This study has illuminated the profound impact of chronic illnesses on the risk of catastrophic health expenditures (CHE) among elderly households in China. It highlights that chronic diseases are a significant driver of financial vulnerability, particularly in this demographic, which typically faces increased medical needs. Building on previous studies that focused solely on the economic impact of multiple comorbidities, this study breakthroughingly confirms that even a single chronic disease can significantly negatively affect a household's financial situation, increasing the risk of CHE.

Contrary to expectations, existing social health insurance schemes have not effectively mitigated the risk of CHE. Despite broad coverage, these schemes fail to alleviate the financial burdens faced by the elderly, particularly those with chronic conditions. The findings of this study urge a recalibration of health and social policies to better protect elderly populations from the devastating impacts of catastrophic health expenditures.By addressing these critical issues, policymakers can ensure a more equitable and sustainable healthcare system that truly supports the needs of China's aging society.

CHARLS

China Health and Retirement Longitudinal Study

CHE

catastrophic health expenditures

standard deviation

confidence interval

odds ratio

Ethics approval and consent to participate

The studies involving human participants were reviewed and approved by the Biomedical Ethics Review Committee of Peking University (IRB0000105IRB00001052–11015). The patients/participants provided their written informed consent to participate in this study.

Consent for publication

Not applicable.

Availability of data and materials

Publicly available datasets were analyzed in this study. This data can be found here: http://charls.pku.edu.cn/.

Competing interests

The authors declare that they have no competing interests.

Funding

This study was supported by the National Natural Science Foundation of China Youth Fund Project (No. 72204048) and Shanghai Philosophy and Social Science Planning Projects (2023EGL002).

Authors' contributions

XY conceived and designed the study, performed the data analysis, and wrote the original draft. DW assisted with data processing and statistical analysis, reviewed numbers and tables, and revised the manuscript.QW and TZ provided revisions to the manuscript and raised constructive questions to optimize this study.QW and TZ refined the study design, oversaw the study implementation and analysis, and revised the manuscript. All authors read and approved the final version of the manuscript.

Acknowledgements

We express our sincere gratitude to China Health and Retirement Longitudinal Study (CHARLS). Thanks to all authors who contributed to this study.

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No competing interests reported.

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Chronic Diseases and Catastrophic Health Expenditures in Elderly Chinese Households: A Cohort Study

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Methods

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Dependent variable

Independent variable

Household and respondent characteristic

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Determinants of catastrophic health expenditure

Results of the Stratification Analyses

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