Healthcare costs attributable to noncommunicable diseases: a longitudinal study based on the elderly population in China

doi:10.21203/rs.3.rs-1949007/v1

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Healthcare costs attributable to noncommunicable diseases: a longitudinal study based on the elderly population in China

https://doi.org/10.21203/rs.3.rs-1949007/v1

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Background

The burden of disease and economic losses caused by aging populations and non-communicable chronic diseases (NCD) are significant public health concerns. Estimates of healthcare costs attributed to chronic diseases in the senior population can inform the creation of disease preventive and control policies. This study therefore utilized an econometric method to estimate the chronic disease attributable fraction (CDAF) of yearly per capita healthcare costs in older persons, which includes all potential costs.

Methods

This study employed the three waves of panel data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The data evaluate the annual per capita utilization and cost of outpatient and inpatient healthcare for the elderly. A two-part model was utilized to estimate outpatient, inpatient, and healthcare costs associated to the six selected chronic conditions.

Results

The top six chronic diseases of the surviving elderly in China are hypertension, arthritis, heart disease, cataract, chronic lung disease, stroke or cardiovascular disease (CVD). The CDAF for outpatient costs, inpatient costs, and healthcare costs were 44.99%, 64.73%, and 55.18%, respectively. Among them, the CDAFs of hypertension in outpatient costs and total healthcare costs were 12.53% and 12.50%; the CDAF of arthritis in outpatient costs was 5.95%; the CDAFs of heart disease in outpatient costs, hospitalization costs and healthcare costs were 17.85 %, 33.84%, and 24.49% respectively; the CDAFs of cataract in outpatient costs and healthcare costs were 4.60% and 5.67%; the CDAFs of chronic lung disease in outpatient costs, inpatient costs, and healthcare costs were 7.50%, 17.03%, and 11.96%; CDAFs of stroke or CVD in outpatient cost, inpatient cost, and healthcare cost were 7.96%, 23.54%, and 16.94%. In addition, gender, place of residence, and degree of education affect the cost attribute to chronic disease in older persons.

Conclusion

In the healthcare service cost of the elderly, the attributed cost of chronic diseases has significant differences, mainly reflected in the elderly's gender, living environment, and preference for outpatient or inpatient treatment. Based on this, the prevention and treatment policies formulated for specific chronic diseases can help reduce the health and economic burden of the society.

elderly

non-communicable chronic diseases

healthcare costs

panel data

two-part model

China

From a world viewpoint, the aging of the population and the alteration of disease spectrum have fueled the continuous increase of demand for health services and had a significant impact on social and economic development. On the one hand, as a result of the rapid expansion of social economy, population structure is also shifting, and all nations face the challenge of aging to varied degrees. The newest Information from the seventh national census of China, issued by the National Bureau of Statistics of China in May 2021, revealed that 18.7% of the population is over 60 years old, and 13.5% is over 65 [1]. A shift in the disease spectrum is one of the alterations brought about by a rapidly aging population. The elderly is most susceptible to chronic diseases. According to statistics, by the end of 2019, out of 254 million elderly people in China, around 120 million elderly people suffer from chronic diseases, and approximately 40.63 million elderly people are crippled or semi-impaired [2]. The direct healthcare costs of the elderly have exacerbated the economic burden of social development in China, which is "growing old before getting rich".

On the other hand, several studies have shown that the current socioeconomic burden of disease is concentrated in non-communicable diseases [3–7]. Global samples from the 2017 Global Burden of Diseases, Injuries, and Risk Factors Study (GBD 2017) were reported. In 2017, non-communicable diseases (NCDs) were responsible for 73.4% of all fatalities, an increase of 7.61 million deaths from NCDs compared to 2007 [8]. Disability-adjusted life years increased dramatically worldwide in 2019 compared to 2009, with NCDs (ischemic heart disease, diabetes, stroke, chronic kidney disease, lung cancer, and age-related hearing loss) being the primary cause [9]. In addition to posing a significant danger to national development and economic progress, the prevalence of NCDs among the elderly exacerbates poverty for patients and their families. The study on population aging and economic burden from developed countries found that population aging would increase the per capita total medical cost of the United States from $2,093 in 2000 to $3543 in 2050, with kidney disease, heart and vascular disease, and urinary system disease experiencing the greatest cost increases [10]. Arthritis, asthma and back problems have the highest incidence rates of chronic diseases among Australian aged 65 and older. The annual medical cost per capita of patients with one primary chronic disease is significantly higher (6,801 Australian dollars) than that of people without chronic disease (5,206 Australian dollars). Moreover, with the increase of comorbidities, the annual cost per person increased for those with two chronic diseases ($7,987) and those with three or more chronic diseases ($8,858) [11]. In addition, the similar pattern can be found in developing nations. Chronic diseases account for 63.96% of the total personal medical cost incurred by senior citizens in rural China. Chronic diseases can raise the utilization rate of healthcare by 1.74 times and the annual medical expenditure per capita by 88% compared with those without chronic diseases [12]. Aging populations and the economic burden of NCD are particularly severe in underdeveloped nations due to inadequate healthcare systems and lagging economic and social growth [13, 14].

To design targeted and effective intervention strategies, it is crucial to assess the incidence and severity of certain noncommunicable diseases in older populations. Taulant Muka reviewed 153 studies worldwide and found cancer and cardiovascular disease have the largest yearly direct expenses per capita among all included NCDs, with estimated costs as high as $197,772 and $81,096 per individual, respectively [15]. In 2017, the annual per capita cost of diabetes-related healthcare in the United States was $13,239, and seniors aged 65 and older were responsible for nearly 61% of this cost [16]. Similarly, the per capita annual cost related to diabetes in South Korea for individuals aged 65 and above was $4,090 in 2019 [17]. It is evident that the health and economic impacts of the same chronic conditions on the elderly in different countries vary. In this instance, quantifying the healthcare costs attributable to specific NCDs can facilitate a more precise ranking of NCD priority.

Consequently, this study constructed panel data sets using CLHLS data from 2011,2014, and 2018, the three most recent phases to be published. The annual utilization and annual costs of outpatient, inpatient and healthcare services for the top six non-communicable chronic diseases affecting China’s older population were estimated. Prior studies on NCDs have not focused on the elderly population, nor have they estimated or reported chronic disease-related healthcare costs. This study fills this gap by employing update data on the prevalence of chronic diseases and their associated economic consequences among older persons. Furthermore, we employ an econometric approach, which yields more robust estimates of attributable costs; the findings will aid in forecasting, planning, and developing cost-effective and sustainable initiatives.

1 Data source

The data used in this study were obtained from The Chinese Longitudinal Healthy Longevity Survey (CLHLS), an ongoing open cohort study of the elderly jointly conducted by Peking University Center for Healthy Aging and Development and National Development Institute. The survey collected health-related information on Chinese seniors aged 65 and older in 23 provinces in China, including socio-demographic characteristics, socioeconomic status, cognitive function, lifestyle, ability to perform daily activities, health status, and healthcare utilization, etc. The goal of the survey is to investigate the factors related to the health and longevity of the Chinese population. Details of CLHLS can be accessed elsewhere [18]. The biomedical ethics committee of Peking University approved the study (IRB00001052-13074), and all participants or their proxies provided written informed consent.

1998 was the year that the CLHLS baseline survey was conducted, followed by 2000,2002,2005,2008,2011,2014,2018. Among these, the survey content of healthcare cost varied in different waves. From 1998 to 2008, only the total healthcare costs of respondents in the past year were investigated. After 2011, costs incurred by outpatients and inpatients were analyzed. From the viewpoints of outpatient, inpatient, and healthcare services, In this study, we examined the impact of different chronic diseases on the healthcare utilization and healthcare costs among the elderly in this study.

As a result, we selected the data from the three most recent periods of CLHLS, namely, the data of 2011, 2014, and 2018, and retained the elderly who were surveyed in all three periods as the research sample. After removing missing and outlier values for key variables, the number of observations used for analysis was 5511 (1837 individuals each year).

2 Measurement

2.1 Healthcare utilization and costs

In terms of healthcare costs, outpatient costs (including registration, outpatient examinations, drugs, outpatient treatment, and all other ambulatory medical expenses), inpatient costs (including post-hospital examinations, surgical and non-surgical treatment, drugs, escort, and hospital costs), and healthcare costs (the sum of outpatient and inpatient costs) were included in our analysis.

We developed dummy variables for whether individual used healthcare services based on their healthcare costs, including whether they use outpatient services (in indicator of positive outpatient costs), whether they use inpatient services (an indicator of positive inpatient costs), and whether they use healthcare services (an indicator of positive healthcare costs).

2.2 Chronic disease

We selected the top six chronic diseases with the highest prevalence in our sample, including Hypertension, Arthritis, Heart disease, Cataracts, Chronic lung disease (bronchitis or emphysema or asthma or pneumonia), and Stroke or Cerebrovascular disease (CVD) to conduct cost attribution analysis. In this study, the primary explanatory variables were the dummy variables for these six chronic diseases (1 indicates having the chronic disease, 2 indicates not having the chronic disease).

2.3 Covariates

Referring to existing studies [12, 19, 20], we controlled for a number of variables that influence the utilization and cost of healthcare services for the elderly in the model, including age, gender (male = 0, female = 1), residence (rural = 0, urban = 1), education level (primary and below = 0, middle and above = 1), marital status (other = 0, cohabited = 1), health insurance coverage (no = 0, yes = 1), smoking status (none = 1, quit = 2, still = 3), drinking status (none = 1, quit = 2, still = 3), body mass index (BMI) (underweight = 1, normal weight = 2, overweight = 3, obesity = 4), activities of daily living (ADL), annual household income per capita.

The educational level was categorized into two groups according to the years of education, primary and below (≤ 6 years) and middle and above (> 6 years); BMI was determined as the weight in kilograms divided by the height in meters squared, kg/m². The criteria for the BMI was adopted “The guidelines for prevention and control of overweight and obesity in Chinese adults” [21]. It was specifically divided into four groups: underweight (< 18.5kg/m²), normal weight (18.5-23.9kg/m²), overweight (24.0-27.9kg/m²) and obesity (≥ 28.0kg/m²). ADL is used to evaluate the daily activities of the elderly, including 1) Bathing, 2) Dressing, 3) Toilet, 4) Indoor Transfer, 5) Continence, and 6) Eating [22]. Each item is categorized as 0 (Completely independent) or 1 (Needs help). The total ADL score ranged from 0 to 6, with higher values suggesting more limited activities of daily living.

3 Statistical analyses

First, descriptive statistics were employed to analyze the basic characteristics of participants over years. Frequency/percentage and mean/standard deviation (SD) were employed to characterize categorical and continuous variables, respectively.

Then, to further investigate the influence of chronic diseases on healthcare costs of the elderly, we referred to studies on the impact of smoking [23] or obesity [24] on healthcare costs and developed the following two-part random effects model. To investigate the influence of chronic diseases on healthcare utilization and cost in older adults.

$$\text{D}\text{E}{\text{x}\text{p}}_{\text{i}\text{t}}={{\gamma }}_{0}+\sum {{\gamma }}_{\text{j}}{\text{C}\text{h}\text{r}\text{o}\text{n}\text{i}\text{c}}_{\text{i}\text{t}}+{{\gamma }}_{7}{\text{X}}_{\text{i}\text{t}}+{{\gamma }}_{8}{\text{Y}}_{\text{i}\text{t}}+{{\gamma }}_{9}{\text{Z}}_{\text{i}\text{t}}+{{\alpha }}_{\text{i}}+{\text{u}}_{\text{i}\text{t}}$$

$$\text{I}\text{n}{\text{E}\text{x}\text{p}}_{\text{i}\text{t}}={{\beta }}_{0}+\sum {{\beta }}_{\text{j}}{\text{C}\text{h}\text{r}\text{o}\text{n}\text{i}\text{c}}_{\text{i}\text{t}}+{{\beta }}_{7}{\text{X}}_{\text{i}\text{t}}+{{\beta }}_{8}{\text{Y}}_{\text{i}\text{t}}+{{\beta }}_{9}{\text{Z}}_{\text{i}\text{t}}+{{{\alpha }}^{{\prime }}}_{\text{i}}+{{\text{u}}^{{\prime }}}_{\text{i}\text{t}}$$

Equation 1 examines the effect of chronic disease on healthcare utilization among older adults, and Eq. 2 explores the effect of chronic disease on healthcare costs for older adults. $\text{D}\text{E}{\text{x}\text{p}}_{\text{i}\text{t}}$ is a dummy variable indicating whether the individual used healthcare services (whether it is a positive healthcare cost); $\text{I}\text{n}{\text{E}\text{x}\text{p}}_{\text{i}\text{t}}$ is the logarithm of healthcare costs for older adults with positive healthcare costs; ${\text{C}\text{h}\text{r}\text{o}\text{n}\text{i}\text{c}}_{\text{i}\text{t}}$ is the six chronic diseases with the highest incidence mentioned above; ${\text{X}}_{\text{i}\text{t}}$is the sociodemographic characteristics of the individual; ${\text{Y}}_{\text{i}\text{t}}$ is the socioeconomic status of the individual; ${\text{Z}}_{\text{i}\text{t}}$ is a variable related to an individual's health; ${{\alpha }}_{\text{i}}$ and ${{{\alpha }}^{{\prime }}}_{\text{i}}$ represent the constant random heterogeneity of the i^th individual; ${\text{u}}_{\text{i}\text{t}}$ and ${{\text{u}}^{{\prime }}}_{\text{i}\text{t}}$ represent the random disturbance terms of Eq. (1) and Eq. (2), respectively. Since the dependent variables of Eq. (1) are dummy variables of three classifications (whether outpatient service is utilized, whether hospitalization is utilized and whether healthcare is utilized), Eq. (1) is estimated using random effects Logit model, whereas Eq. (2) is estimated using random effects generalized least squares model.

In addition, we used the parameters acquired by fitting the two models to predict healthcare costs in both the chronic disease presence and absence scenarios. Referring to the existing study [24, 25], first, the estimated parameters were used to predict the annual per capita healthcare cost of the elderly based on the actual situation, as an actual value (${\widehat{\text{Y}}}_{\text{i}}^{\text{A}}$). Then, we predict the healthcare cost of the elderly without the chronic disease as a counterfactual value (${\widehat{\text{Y}}}_{\text{i}}^{\text{C}\text{F}}$) by setting the parameter of the chronic disease to 0 (assuming that the elderly do not have the chronic disease) and all other characteristics remain the same. The chronic disease attributable fraction (CDAF) can be calculated based on the predicted actual value and the counterfactual value using Eq. 3.

$$\text{C}\text{D}\text{A}\text{F}=\frac{{\widehat{\text{Y}}}_{\text{i}}^{\text{A}}-{\widehat{\text{Y}}}_{\text{i}}^{\text{C}\text{F}}}{{\widehat{\text{Y}}}_{\text{i}}^{\text{A}}}$$

The p-value less than 0.05 could be identified as statistical significance. All data were collated and analyzed using STATA version 16.0 (Stata Corp, College Station, TX, USA).

1 Characteristics of participants

Participants’ Characteristics were listed in Table 1. This study included hypertension, arthritis, heart disease, cataract, chronic lung disease and Stroke or CVD, which ranked the top six among the elderly, with prevalence rates of 30.65%, 18.40%, 11.49%, 9.69%, 9.42% and 6.53% in 2011, respectively. As the chronic disease with the highest prevalence, the prevalence of hypertension in the three waves were 30.65%, 35.11% and 37.45%, respectively. The prevalence of all chronic diseases exhibited an upward tendency as age increased, year after year. In 2011, the average age of the elderly was 77.44 ± 8.38 years old, and the distribution of gender characteristics was balanced: 51.06 percent of samples were male and 48.94 percent were female. Among them, 86.61% lived in rural areas, 84.05% had a education or less, 89.77% had health insurance, 58.68% lived with a partner, and the average ADL score was 0.08 ± 0.44. Due to widowhood, divorce, and other factors, the proportion of old individuals living alone increases with age, while the elderly's daily activities increasingly decline. In addition, the proportion of the elderly who were overweight or obese in 2011 was 22.43% and 6.26%, respectively. From 2011 to 2018, the proportion of the elderly who were overweight and obese climbed, while the proportion of the elderly who smoked and drank declined progressively, but did not change much.

Table 1

Descriptive Statistics of Study Sample, CLHLS, 2011, 2014 and 2018
Type of variable	Level of variable	2011	2014	2018
Hypertension	Yes	563 (30.65)	645 (35.11)	688 (37.45)
Arthritis	Yes	338 (18.40)	265 (14.43)	223 (12.14)
Heart disease	Yes	211 (11.49)	232 (12.63)	292 (15.90)
Cataracts	Yes	178 (9.69)	226 (12.30)	232 (12.63)
Chronic lung disease	Yes	173 (9.42)	203 (11.05)	228 (12.41)
Stroke or CVD	Yes	120 (6.53)	144 (7.84)	198 (10.78)
Gender	Male	938 (51.06)
	Female	899 (48.94)
Age		77.44 (8.38)	80.06 (8.38)	84.01 (8.39)
Residence	Rural	1591 (86.61)	1594 (86.77)	1557 (84.76)
	Urban	246 (13.39)	243 (13.23)	280 (15.24)
Education level	Primary and below	1544 (84.05)
	Middle and above	293 (15.95)
Marital status	Cohabited^a	1078 (58.68)	994 (54.11)	847 (46.11)
	Other^b	759 (41.32)	843 (45.89)	990 (53.89)
BMI	Underweight	256 (13.94)	236 (12.85)	277 (15.08)
	Normal weight	1054 (57.38)	1046 (56.94)	994 (54.11)
	Overweight	412 (22.43)	442 (24.06)	436 (23.73)
	Obesity	115 (6.26)	113 (6.15)	130 (7.08)
Smoking status	None	1153 (62.77)	1213 (66.03)	1207 (65.70)
	Quit	280 (15.24)	248 (13.50)	308 (16.77)
	Still	404 (21.99)	376 (20.47)	322 (17.53)
Drinking status	None	1198 (65.22)	1298 (70.66)	1303 (70.93)
	Quit	241 (13.12)	189 (10.29)	227 (12.36)
	Still	398 (21.67)	350 (19.05)	307 (16.71)
Health insurance coverage	No	188 (10.23)	143 (7.78)	234 (12.74)
	Yes	1649 (89.77)	1694 (92.22)	1603 (87.26)
Activities of daily living		0.08 (0.44)	0.12 (0.52)	0.41 (1.11)
Annual household income per capita		10741.86 (14802.52)	13410.80 (16832.71)	17782.14 (21385.71)
Sample size		1837	1837	1837
Note, ^aCohabited covers married and cohabitating; ^bOther covers single, separated, divorce, and widowed

2 The effect of chronic diseases on healthcare utilization and costs among Chinese elderly

After controlling for other factors influencing healthcare utilization and cost in older adults, the results of the two-part model indicated that compared with counterparts, having hypertension (OR = 1.660, p < 0.001), arthritis (OR = 1.956, p < 0.001), heart disease (OR = 2.266, p < 0.001), cataract (OR = 1.449, p < 0.01), chronic lung disease (OR = 1.940, p < 0.001), stroke or CVD (OR = 2.221, p < 0.001) were significantly associated with higher annual healthcare utilization in older adults; Among older adults who utilized healthcare services, hypertension (β = 0.196, p < 0.01), heart disease (β = 0.755, p < 0.001), cataracts (β = 0.214, p < 0.01), chronic lung disease (β = 0.535, p < 0.001), stroke or CVD (β = 0.739, p < 0.001) increased the health care cost of the elderly in different degrees, whereas there is no statistically significant relationship between arthritis (p > 0.05) and healthcare cost (Table 2).

According to the breakdown analysis results of the outpatient and inpatient outcomes. Six chronic diseases increase the utilization and cost of outpatient services for senior citizens to varied degrees. Hypertension (OR = 1.307, p < 0.01), heart disease (OR = 1.812, p < 0.001), cataract (OR = 1.175, p < 0.05), chronic lung disease (OR = 2.109, p < 0.001), stroke or CVD (OR = 2.883, p < 0.001) increased the utilization of inpatient services among the elderly, with heart disease (β = 0.731, p < 0.001), chronic lung disease (β = 0.342, p < 0.01), stroke or CVD (β = 0.384, p < 0.001) significantly increasing the cost of hospitalization for the elderly.

Table 2

Parameter estimates and test statistics, CLHLS, 2011, 2014 and 2018
Type of Chronic disease	Outpatient visits logit OR (std. Err)	Log of outpatient expenditures GLS β (std. Err)	Inpatient visits logit OR (std. Err)	Log of inpatient expenditures GLS β (std. Err)	Health service logit OR (std. Err)	Log of healthcare service expenditures GLS β (std. Err)
Hypertension	1.570***	0.188**	1.307**	0.001	1.660***	0.196**
	(0.145)	(0.063)	(0.104)	(0.113)	(0.182)	(0.064)
Arthritis	1.942***	0.174***	1.040	-0.038	1.956***	0.079
	(0.279)	(0.049)	(0.099)	(0.139)	(0.266)	(0.052)
Heart disease	1.807***	0.566***	1.812***	0.731***	2.266***	0.755***
	(0.199)	(0.079)	(0.173)	(0.140)	(0.196)	(0.111)
Cataracts	1.311**	0.176**	1.175*	0.226	1.449**	0.214**
	(0.127)	(0.060)	(0.086)	(0.128)	(0.161)	(0.072)
Chronic lung disease	1.753***	0.345***	2.109***	0.342**	1.940***	0.535***
	(0.212)	(0.064)	(0.275)	(0.112)	(0.284)	(0.085)
Stroke or CVD	1.642***	0.392***	2.883***	0.384***	2.221***	0.739***
	(0.227)	(0.057)	(0.333)	(0.080)	(0.246)	(0.064)
Covariate dummies	YES	YES	YES	YES	YES	YES
Province dummies	YES	YES	YES	YES	YES	YES
Year dummies	YES	YES	YES	YES	YES	YES
Note, *p < 0.001, p < 0.01, *p < 0.05

3 Predictions of healthcare costs

Overall, the total CDAF is 55.18%. With the exception of arthritis (which is not statistically significant in the healthcare costs model in Table 2), the chronic diseases with CDAF from high to low were heart disease, stroke or CVD, hypertension, chronic lung disease, and cataract. Annual per capita healthcare costs attributable to heart disease is 358.235 CNY, with a CDAF of 24.49%; annual per capita healthcare costs attributable to stroke or CVD are 247.811CNY, with a CDAF of 16.94%; and the annual per capita healthcare costs attributable to hypertension are 182.751 CNY, with a CDAF of 12.50% (Panel A in Table 3).

Panel B in Table 3 showed the breakdown analysis of the outpatient costs. Chronic diseases were responsible for 44.99% of the total outpatient costs incurred by the elderly. Among them, the CDAF ranked heart disease, hypertension, stroke or CVD, arthritis, chronic lung disease and arthritis. The heart disease outpatient cost CDAF was 17.85%. The annual per capita outpatient cost of the elderly would decrease by 126.861 CNY if there was no heart disease and all other characteristics remained unchanged. The CDAF of hypertension outpatient costs was 12.53%, and the annual per capita outpatient cost attributed to hypertension was 89.047 CNY, significantly greater than arthritis, cataract, chronic lung disease, stroke or CVD.

In the analysis of hospitalization, the CDAF of hospitalization costs owing to heart disease was 33.84%, and the per capita annual hospitalization cost attributable to heart disease was 401.706 CNY. CDAF of stroke or CVD was 23.54%, and the yearly hospitalization cost per capita was 279.447 CNY. These are the two most prevalent chronic diseases that drive up hospitalization costs. In addition, 17.03% hospitalization costs were attributable to chronic lung disease, resulting in an increase of 202.183 CNY per capita in annual hospitalization costs (Panel C in Table 3).

Table 3

Estimated personal medical cost attributed to chronic disease (CNY)
Type of Chronic disease	Predicted expenditure	Counter factual expenditure	Expected cost of disease	CDAF %	T-statistics
Panel A: Total
Hypertension	1462.548	1279.797	182.751	12.50	28.960***
Arthritis	1462.548	1415.452	47.096	3.22	20.266***
Heart disease	1462.548	1104.312	358.235	24.49	19.118***
Cataracts	1462.548	1379.629	82.919	5.67	15.136***
Chronic lung disease	1462.548	1287.592	174.956	11.96	15.920***
Stroke or CVD	1462.548	1214.737	247.811	16.94	14.501***
ALL	1462.548	655.586	806.962	55.18	26.887***
Panel B: Outpatient
Hypertension	710.595	621.548	89.047	12.53	33.131***
Arthritis	710.595	668.299	42.296	5.95	21.245***
Heart disease	710.595	583.734	126.861	17.85	20.746***
Cataracts	710.595	677.940	32.655	4.60	17.155***
Chronic lung disease	710.595	657.335	53.260	7.50	17.762***
Stroke or CVD	710.595	654.049	56.546	7.96	15.012***
ALL	710.595	390.922	319.673	44.99	31.599***
Panel C: Inpatient
Hypertension	1187.184	1108.103	79.081	6.66	16.662***
Arthritis	1187.184	1193.995	-6.810	-0.57	-7.823***
Heart disease	1187.184	785.478	401.706	33.84	12.748***
Cataracts	1187.184	1094.946	92.238	7.77	9.267***
Chronic lung disease	1187.184	985.001	202.183	17.03	10.332***
Stroke or CVD	1187.184	907.737	279.447	23.54	10.660***
ALL	1187.184	418.764	768.420	64.73	16.583***
Note, ***p < 0.001

CNY: Chinese Yuan (1 Chinese Yuan = 0.149 US Dollar)

4 Results of Heterogeneity Analysis

To further examine differences in healthcare costs attributable to chronic diseases among older persons by gender, education level, and place of residence, we subdivided based on a variety of characteristics and applied the same calculation procedure as mentioned above. Estimates of healthcare costs attributable to chronic diseases among older persons with various characteristics. The results were shown in Fig. 1.

The yearly per capita total healthcare costs attributed to chronic diseases are 899 CNY for males and 800 CNY for females, a rather modest variation. For certain chronic diseases, however, the annual per capita healthcare costs attributable to hypertension are significantly higher in female than in male; For cataracts, chronic lung disease, stroke or CVD, the annual per capita healthcare costs attributable to male are higher than female; There was no significant difference between male and female in healthcare costs attributable to heart disease, and similar trends were observed in outpatient and inpatient costs. Second, in terms of education level, the annual per capita healthcare costs attributable to chronic diseases are significantly higher seniors with a secondary education or higher than those with a primary education or less, and similar results are obtained for outpatient and inpatient costs attributable to specific chronic diseases. In addition, according to the results of urban-rural heterogeneity analysis, the annual per capita healthcare costs attributable to chronic diseases among the elderly living in urban were significantly higher than those living in rural (urban 2399.60 CNY vs. rural 589.00 CNY), with the exception of the outpatient cost of chronic lung disease and the attributable cost of other chronic diseases.

Based on a cohort study of the senior population, this study evaluated the healthcare costs of the six chronic diseases with the highest prevalence among the elderly in China, and found that the healthcare costs attributable to chronic diseases accounted for 55.18% of the total healthcare costs of the elderly. Clearly, chronic diseases impose both health and financial hardships on the elderly. With rising age, the prevalence of hypertension, heart disease, chronic lung disease, cataract, stroke or CVD all exhibited an upward trend, which was consistent with the disease profile of the elderly as determined by many studies [26–29]. However, the prevalence of arthritis tends to decline with age, presumably as a result of the increasing use of cleaner, healthier fuels for cooking and heating in place of more polluting solid fuels as the civilization evolves. The use of solid fuels for cooking and heating indoors was associated with an increased risk of arthritis in middle-aged and older rural persons, according to the findings of a countrywide population-based cohort study [30]. The results of the heterogeneity analysis further indicated that outpatient costs attributable to arthritis were statistically significant for rural older persons but not for urban older adults. In addition, arthritis is frequently accompanied by pain and dysfunction during activity [31], which leads to relatively early treatment of arthritis in the elderly or irreversible outcomes (such as disability, etc.), resulting in a shorter duration of the disease.

In terms of specific chronic diseases, hypertension has the highest prevalence, and its treatment consists primarily of long-term medicine to manage and reduce blood pressure [32]. Consequently, the majority of its healthcare costs were attributable to outpatient services; the CDAF for outpatient costs among the elderly is 12.53%. Additionally, due to the characteristics of hypertension requiring long-term maintenance and the poor disease management ability of the elderly [33], the course of hypertension is prolonged, resulting in a rise in healthcare costs, with a CDAF of 12.50%. Multiple studies have demonstrated that the low rate of pretension control is the main reason for its high prevalence and healthcare costs [34–37]. Improving the effectiveness of self-management for hypertensive patients is the focus of the current intervention. Heart disease, stroke or CVD, and chronic lung disease accounted for 24.49%,16.94%, and 11.96% of total health care costs, respectively. The majority of the costs attributable to stroke or CVD and chronic lung disease were connected with hospitalization. While many chronic diseases can be prevented and alleviated with daily medication, they carry the danger of acute exacerbation and severe consequences, such as stroke, cerebral infarction, asthma, COPD, etc., thus hospitalization is also required. A population-wide study conducted in the United States revealed that asthma-related hospital expenditures fell from 2008 to 2013, whereas prescription medicine costs climbed [5]. Possible explanation for the difference between China and The United States may be the difference in asthma treatment. The United States is more inclined to limit the risk of acute exacerbation through long-term use of short-acting medicines [38], but the elderly in China has inadequate self-management skills and may therefore prefer treatment primarily in the acute stage. Consistent with the findings of earlier studies, the majority of healthcare costs associated with brain diseases are in hospitalizations [39, 40]. The inpatient medicine costs associated with stroke accounted for more than one-third of the total hospitalization expenditures [39]. For stroke or cerebrovascular disease and chronic lung disease, it is more crucial to prevent acute exacerbation.

Heart disease accounted for the highest proportion of healthcare costs for the elderly (CDAF = 24.49%), and its CDAF ranks top for both outpatient costs (17.85%) and inpatient costs (33.84%). This represented a significant financial burden for both patients and healthcare systems. Consistent with previous studies, as the prevalence of heart disease rises, so does the rate of hospitalization [41], primarily for acute exacerbation requiring short-term therapy. In addition, cardiac disease frequently presents with complications. For instance, hypertension is a major risk factor for heart disease [42, 43], and the treatment of heart disease frequently necessitates additional healthcare costs for blood pressure control, oral disease therapy, blood glucose and lipid control, etc. [44, 45]. Outpatient costs linked to heart disease increased with the treatment of comorbidities and medications for heart disease. Consequently, preventing underlying illnesses and minimizing the likelihood of acute aggravation is necessary to reduce the enormous health loss and economic burden imposed by heart disease. The findings of this study indicated that healthcare costs for the treatment of arthritis and cataract are concentrated in outpatient services and are comparable across nations [46]. Arthritis is initially treated conservatively with anti-inflammatory medications to alleviate inflammation, and joint replacement can be undertaken after severe injury; Hence, the majority of arthritis-related healthcare costs are associated with drugs. Cataract is the leading cause of blindness in the elderly and is treated surgically [47]. Nevertheless, cataract surgery does not typically necessitate hospitalization. Reducing the risk factors associated with these two diseases is a realistic preventive measure.

According to the results of heterogeneity analysis, the chronic healthcare costs of urban seniors are higher than those of rural seniors, which is consistent with previous research findings [12, 48, 49]. Due to the relatively lower income, rural elderly has a lower rate of healthcare service consumption. Combined with the lack of medical resources, diseases are frequently inadequately diagnosed and treated. Consequently, chronic healthcare for the elderly in rural locations are less expensive, but they suffer more severe injuries [12]. Gender differences in chronic diseases must be taken into account. Women have a higher risk of cardiovascular disease, while men have a higher incidence of cerebrovascular disease due to variations in physical traits. To further complicate matters, as various sex hormones respond differently to drugs and other therapies, there are gender differences in disease progression and exacerbation, as well as in the burden of disability and death [29, 50, 51], and this is also shown in individuals with chronic lung disease and chronic kidney disease [52–54]. This may explain why the economic and mortality burdens of the same disease are different for older persons of different genders. Consequently, gender differences should be considered in the prevention and treatment of chronic diseases, and personalized programs may be more effective.

Improving the self-management efficiency of the elderly is the key to chronic illness prevention and improvement methods for the elderly, which can be enhanced and guided from the following aspects: 1) Lifestyle: smoking, alcohol consumption, unhealthy diet and lack of physical activity are modifiable risk factors for multiple chronic diseases [55]; adopting a healthy lifestyle can effectively lower the risk of chronic diseases in the elderly, preferably beginning at a younger age; 2) Disease management: Increasing medication adherence among the elderly is an effective intervention that can alleviate and improve the symptoms of most chronic diseases and lower the likelihood of acute exacerbations. If necessary, artificial intelligence, remote monitoring and other technologies can be utilized to enhance the capacity for drug management [56, 57]; 3) Social support: the assistance and guidance of family members, peers and medical staff has a positive effect on patients' long-term self-care, increasing patients' self-regulation ability and self-efficacy [58]; 4) Medical care system: establish a complete three-level prevention strategy, improve the coverage and acceptance of primary health care, establish aids for chronic diseases in communities and villages, provide a more perfect chronic disease management process, and apply modern Internet technology to increase medical resources in less developed areas [59]. In addition, the influence of sociodemographic and economic factors, particularly gender differences, should be taken into account throughout the entire process of prevention and treatment of chronic diseases.

There are several limitations to this study. First of all, as the data of this study were obtained from a public database, the classification of chronic diseases is established; the degree of disease classification refinement is poor, and the CDAF cannot be completely compared and discussed. The second limitation on the generalizability of the findings is that the focus of this study is on the geriatric population. Lastly, normal diagnostic procedures for chronic diseases were not adopted. Therefore, the prevalence of chronic diseases is self-reported by participants, which may differ slightly from the actual situation. Nevertheless, our research and discussion of chronic disease- related healthcare costs of the elderly can provide some guidance for disease prevention and treatment, and have some reference relevance for improving the quality of life of the elderly.

In China, chronic diseases impose a substantial economic and health burden to the elderly. The study revealed that different chronic diseases have their unique preventative and treatment obstacles. Therefore, the development of targeted programs based on a comprehensive consideration of disease risk factors can enhance the health of the elderly and minimize the financial burden on patients and the healthcare system.

NCD: non-communicable diseases; CDAF: chronic disease attributable fraction; CLHLS: the Chinese Longitudinal Healthy Longevity Survey; CVD: cardiovascular disease; GBD: Global Burden of Diseases, Injuries, and Risk Factors Study; COPD: chronic obstructive pulmonary disease

Ethics approval and consent to participate

The biomedical ethics committee of Peking University approved the study (IRB00001052-13074), and all participants or their proxies provided written informed consent. All methods were carried out in accordance with relevant guidelines and regulations or Declaration of Helsinki.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and analyzed during the current study are available from Peking University Open Research Data Platform. (https://opendata.pku.edu.cn/dataset.xhtml?persistentId=doi:10.18170/DVN/WBO7LK). The full datasets used in this analysis are available from the corresponding author upon reasonable request.

Competing interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

This study was supported by the Cultivation Project of Decision-making Consultation, Institute of Healthy Jiangsu Development, Nanjing Medical University (7).

Author's contribution

HY and XPX designed the study and critically reviewed, commented, and revised important intellectual content. SQZ and LPZ performed the final statistical analyses and interpretation of data and drafted the article. XPX revised the draft grammatical sentences.

Acknowledgements

Not applicable.

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Healthcare costs attributable to noncommunicable diseases: a longitudinal study based on the elderly population in China

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