Inequalities in Resource Distribution and Healthcare Service Utilization of Long-Term Care in China

This study uses social services data from the China Civil Affairs Statistical Yearbook from 2014 to 2018, which records statistics related to social elderly service institutions in 31 provinces of China from 2013 to 2017, covering municipalities directly under central government authority and autonomous regions in mainland China. Data for Taiwan, Hong Kong, and Macao are not included in this study. The 31 provinces were divided into three regions according to their geographical distribution and GDP per capita: the Western (undeveloped) region covering Inner Mongolia, Ningxia, Gansu, Shaanxi, Sichuan, Chongqing, Guizhou, Yunnan, Guangxi, Qinghai, Xinjiang, and Tibet; the Central (developing) region covering Heilongjiang, Jilin, Shanxi, Henan, Anhui, Hubei, Jiangxi, and Hunan; and the Eastern (developed) region covering Beijing, Tianjin, Hebei, Liaoning, Shandong, Jiangsu, Zhejiang, Shanghai, Fujian, Guangdong, and Hainan [30]. Population and disposable income per capita data for the corresponding years are obtained from the China Statistical Yearbook.

Most LTC institutions are under the supervision of the Chinese civil affairs authorities. In the civil affairs statistics, institutions affiliated with elderly and disabled people that provide residential services include urban LTC institutions, rural LTC institutions, honorary homes, honorary military rehabilitation hospitals, demobilized military sanatoriums, and military rest homes. The first two are managed by the civil affairs departments, while the rest are managed by the military. Honorary homes are living care institutions exclusively for military personnel and their families. Honorary military rehabilitation hospitals, demobilized military sanatoriums, and military rest homes provide living care and rehabilitation care accommodation for disabled military personnel, demobilized military personnel, and retired cadres of the army, respectively. These four types of institutions provide resources only to military personnel (not to other personnel), and all care costs are covered by the military. According to Chinese media reports, the number of all elderly military cadres in mainland China in 2022 is about 267,000, accounting for only 0.10% of the overall elderly population, and we, therefore, do not include them in our study. Since the 2015 statistical yearbook does not provide separate data for urban and rural areas, we use the five-year average results as a proxy. Four provinces, namely, Hainan (eastern region, the elderly account for 1.13% of the Eastern region), Tibet and Inner Mongolia (western region, the elderly account for 7.14% of the Western region), and Jilin (central region, the elderly accounts for 6.65% of Central region), have serious missing data for resource utilization, and they are therefore excluded from our measurements of inequality of utilization.

The Gini coefficient and the CI are instruments commonly used to measure inequality. The Gini coefficient is a well-known general measure of inequality [31], and the CI is a measure of relative income-related inequality in health, the most commonly used inequality measure index [32]. Whereas the Gini coefficient is used to measure the distribution of LTC resources relative to the size of the elderly population, the CI is used to measure the distribution of LTC resources and service utilization relative to economic status. The Gini coefficient is a quantitative indicator of the degree of uneven distribution of wealth based on the Lorenz curve, which involves ranking a country’s total population in descending order of income, finding the percentage of the population and the corresponding cumulative percentage of resources or services, and depicting the correspondence on a graph. The Gini coefficient is thus a proportional value obtained by dividing the area of the region between the diagonal and the Lorenz curve by the entire area between the diagonal and the horizontal axis:(1)S=12∑i=1n(LRi−1+LRi)×Pi(2)LR0=0(3)G=2×(12−S) where S is the area between the Lorenz curve and the horizontal axis, LRi is the cumulative percentage of LTC resources, and Pi is the proportion of the population in each group ranked from lowest to highest in terms of LTC resources. i depends on the number of provinces considered. G, the Gini coefficient, takes a value from 0 to 1. Referring to the critical value of the Gini coefficient given by the China national bureau of statistics and the classification of the Gini coefficient threshold value in existing literature [33,34]. We divide the cut-off value of the Gini coefficient into a value of 0 denotes absolute equality in the distribution of resources; a value of 1 denotes absolute inequality; a value of G less than 0.3 denotes a preferred equality status; a value greater than 0.4 triggers an inequality alert; and a value exceeding 0.6 reflects a highly inequitable distribution of resources.

CI algebraic expressions are not unique. Drawing on the application of CI in health services, we adopt the formula used in a previous study [34]:(4)CI=2nμcov(LUi,Ri) where Ri is the fractional rank in terms of disposable income per capita. LUi is the LTC utilization indicator, and μ is their mean. The value 2 is included to ensure that the CI ranges from −1 to +1. A value of 0 indicates absolute equality; a negative value indicates a concentration of LTC resources or services in poorer populations; and a positive value represents a concentration of LTC resources or services in richer populations [32]. n depends on the number of provinces considered.

Long-term care is a relatively new concept in China. As for the specific service categories, according to the classification in the government report and the Statistical Yearbook, institutional LTC in China generally includes a range of services such as daily living care (assistance with daily care such as bathing and dressing), professional care (non-therapeutic care and rehabilitation services), and other services aimed at providing long-term support for people who have lost their daily living abilities and cognitive functions. In terms of specific data selection, we refer to previous literature [8,12,33,34,35,36,37] and combine the actual situation of LTC in China to establish a system of indicators to examine the distribution and utilization of LTC (see Table 1).

Most LTC is low-tech, especially in late-developing countries, where greater availability of institutions, beds, and workers plays a key role in securing LTC and quality of life [35]. Therefore, we used three indicators, the number of institutions, beds, and workers, to examine the resource distribution of LTC in China. We operationally convert these three indicators into relative indicators with comparative significance (mean value per 1000 elderly).

Previous studies on LTC utilization have generally considered whether the service has been used as an indicator of service utilization [33,36]. In China, LTC is officially defined in terms of the provision of a series of basic life care and closely related healthcare services for the disabled elderly for a period of time [37]. Considering LTC service is different from therapeutic service in the Chinese context [20], we define healthcare service utilization in institutions specifically in terms of the level of occupancy, and rehabilitation and nursing services utilized by the disabled elderly. Healthcare services utilization is measured in terms of the proportion of disabled residents per 1000 elderly people, and the number of rehabilitation and nursing services per resident.

Table 2 shows that from 2013 to 2017 the number of urban elderly people continued to increase, while per capita resources for LTC grew slowly. The number of institutions increased from 0.11 to 0.12, the number of beds increased from 15.59 to 17.54, and the number of workers increased from 1.76 to 2.12. The availability of beds and workers in the Eastern region was significantly higher than in the Central and Western regions. However, the number of institutions in the Eastern region was decreasing, and the gaps between the regions were narrowing.

In rural areas, the size of the elderly population was also growing, but the development of LTC resources was quite different from urban areas, with an obvious decline over the same period (Table 3). Specifically, the number of institutions decreased from 0.44 to 0.20, the number of beds decreased from 39.28 to 23.19, and the number of workers decreased from 2.37 to 1.54. The same trend of decreasing resources was observed in all three regions. In comparison, rural areas have more institutions and bed resources than urban areas. A rural-urban migrant is difficult to explain the urban-rural disparity of LTC, since rural migrant workers change jobs frequently [38]. A higher number of rural areas may be driven by political support of the continuous governmental resource distribution.

The Gini coefficient for urban areas relative to the elderly population was less variable, ranging from 0.168 to 0.294 (Table 4). The Gini coefficient for the number of institutions ranged from 0.198 to 0.227; for the numbers of beds and workers, it decreased continuously from 0.282 to 0.168 and from 0.294 to 0.206, respectively, indicating greater equality and an overall trend of gradual improvement. The Gini coefficients for the distribution of LTC resources in rural areas relative to the elderly population were more variable, with all three increasing rapidly since 2015 (from 0.027, 0.119, and 0.075, respectively, to 0.184, 0.200, and 0.334), indicating an obvious increase in inequality.

The development of the Gini coefficient from 2013 to 2017 shows that LTC resource distribution in urban areas is improving, but that the distribution in rural areas gives cause for concern. The distribution of urban LTC institutions and beds is relatively equal and improving relative to the size of the aging population (all G-values are less than 0.3 and decreasing). Thus, urban LTC resources have basically reached a low level of equilibrium. The rate of decline in G values, representing rural LTC resources, has slowed. Distributional inequality has increased significantly with the end of policies that tilted resources toward rural areas. The urban-rural differences are shrinking, obviously at the expense of increasing inequality in rural areas. This implies a risk of inequality between urban and rural areas in terms of the size of the distribution of LTC resources as policy interventions wane.

From 2013 to 2017, urban areas provided more LTC resources and healthcare service utilization than rural areas (Table 5), although rural areas have more bed resources. Trends in specific utilization indicators varied, with the gap between urban and rural areas widening for the number of disabled residents per 1000 elderly people, but narrowing for the number of rehabilitation and nursing services per resident.

From 2013 to 2017, the number of urban disabled residents maintained a steady increase (1.71–2.00 per 1000 elderly people), whereas the number of rural disabled residents declined and then rebounded slightly (from 0.80 to 1.16 per 1000 elderly people). Rehabilitation and nursing services per resident in urban areas increased and then decreased (ranging between 2.62 and 3.13 per capita), while rehabilitation and nursing services per resident in rural areas maintained a steady increase (1.30–1.96 per resident). However, this change is not the same as the trend in the number of workers between urban and rural areas. While the number of services is rising in both urban and rural areas, the number of workers in rural areas is declining. This may be closely related to the difference in government purchase of services policies between urban and rural areas.

LTC resources and healthcare service utilization in the Eastern region were much higher than in the Central and Western regions, and the gap widened. In urban areas, the Central region scored lower than the Western region for both LTC resources and healthcare service utilization; in rural areas, the Central economic region scored only slightly higher than the Western region. From 2016, the number of rehabilitation and nursing services per resident in the Western region surpassed that in the Central region. It is worth noting that the above changes exhibit the opposite of the regional economic level status. The central region has a higher level of economic development than the western region, but the western region has a higher utilization of services. The reason for this may be that the lower economic level makes it more common for the young population in the west to work outside their hometowns. This leaves western households with less capacity for services, forcing older adults to seek services in the marketplace.

The CI values for LTC resources and services in both urban and rural areas were positive, implying that LTC resources and healthcare service utilization were concentrated among the richer population in both cases. The CI values for disabled residents in urban areas continued to decline (from 0.483 to 0.329), implying an improvement in equality. The CI values for disabled residents in rural areas increased, remaining above 0.50 for the last three years of the period under study, implying a high level of income-related inequality. Such a time series with a decreasing trend of urban inequality and an increasing trend of rural inequality. There is a similar change to the trend in the Gini coefficient, implying that the improvement in LTC utilization in urban areas is built on the premise of increasing inequality in rural areas. The CI values for urban and rural rehabilitation and nursing services fluctuated but were low overall (ranging from 0.185 to 0.384), indicating reasonable income-related equality (Table 6).

Within different economic zones, more complex income-related inequalities of LTC resources and healthcare service utilization were found (Figure 1). The CI values were positive in the Eastern region and higher in rural areas (ranging from 0.33 to 0.53). The CI values for rehabilitation and nursing services per resident were negative in urban areas in the Central region and rural areas in the Western region, indicating a concentration of resource utilization toward poorer groups. The CI values for rehabilitation and nursing services per resident in urban areas of the Central and Western regions gradually exceeded those in the Eastern region. However, for all other indicators, the Eastern region had higher (absolute) CI values than the Central and Western regions.

From the evolution of CI values, the inequality of resources and utilization exhibited in different economic zones shows a phenomenon of increasing inequality as the socioeconomic level increases. In other words, the differential allocation of resources by the government across regions has not substantially narrowed the gap in the level of services received by the elderly.

We find that rural areas have more institution and bed resources compared to urban areas. The higher base number of institutions and beds in rural areas cannot be explained in terms of economic level and is actually due to continuous policy support dedicated to increasing the number of beds in rural areas. During the 11th Five-Year Plan (2006–2010), the government proposed adding 2.2 million beds in rural institutions for the elderly. In the 12th Five-Year Plan period (2011–2015), the government set a requirement of 30 beds per 1000 elderly people nationwide, with 3.42 million new beds of all types, and increased policy support and resource distribution for rural areas and the Central and Western regions. The 13th Five-Year Plan period (2016–2020) again called for improvements to the supply of services for the elderly but without an emphasis on tilting resources to rural areas. Table 3 shows that the higher distribution of bed resources in rural areas reflects the implementation of these three plans. Previous studies have also observed that the degree of administrative directives and policy support, rather than of market regulation, is what mainly influences the distribution of resources, especially in rural areas [39]. However, in contrast to previous findings that more resources flow to urban areas, our results indicate a flow to rural areas [40]. Moreover, and again in contrast to earlier studies [29], we find that the greater institutional resources in rural areas lead to greater accessibility of care services in rural areas than in urban areas.

Urban areas have more resources for workers, although they have fewer bed spaces. There are no regulations on worker numbers in China in terms of policy, and the distribution of workers is influenced by labor market mechanisms, with higher wages in urban areas likely to attract more workers. Appropriate staffing is critical in the provision of care for the elderly [41], and staffing is often defined by the number of caregivers and the degree to which their caregiving skills match the needs of the elderly population. In terms of the number of caregivers, there is a large gap between China and advanced countries in East Asia with aging populations. In 2017, South Korea had nine caregivers per 1000 elderly people, while Japan had eleven [42]. In contrast to the fixed nature of beds, workers are highly mobile, and a lack of labor contract protection in China contributes to high turnover rates [43]. The higher numbers of beds and lower numbers of workers in rural areas reflect the difficulty of recruiting and retaining staff in rural LTC institutions. Staff shortages, especially of caregivers, lead to a lack of caregiver time apportioned to elderly people, which results in incomplete care [44], with a corresponding increase in adverse events such as medical errors, falls, and pressure sores [45]. In terms of competence, many existing caregivers lack caregiving skills; instead of providing geriatric care, they can meet only the basic needs of elderly people [29,46]. Thus, LTC staffing in China needs to be improved if the LTC needs of the disabled elderly population are to be met.

The level of utilization of LTC resources and healthcare services is low, with large variations between urban and rural areas with different levels of economic development. On the one hand, not only is the level of utilization of LTC resources and services in rural areas much lower than in urban areas but the rise in utilization in urban areas is accompanied by a decline in utilization in rural areas (Table 5). On the other hand, although LTC service utilization in both urban and rural China reflects a pro-rich bias, this inequality is improving in urban areas and rising in rural areas (Table 6). The reason for this phenomenon may be related to the fact that the financial security of LTC services in China is more focused on the urban elderly, resulting in ineffective cost-sharing of LTC medical services. LTC costs are particularly high [47], and there is a large difference in retirement incomes in urban and rural areas. For urban elderly people, the main payers of LTC costs are their pensions and basic healthcare insurance, while the main payers of LTC costs for rural elderly people are their families [48,49], with urban pensions being twenty times as high as rural pensions [50]. Access to pensions for the elderly in rural China has led to a significant decline in rates of co-residence with adult children [51], which is the primary means of accessing LTC for the rural elderly [52], making it difficult for them to access adequate informal care services. Unfortunately, access to pensions, despite being sufficient to have a detrimental impact on informal care, is at too low a level to support the access of rural elderly people to formal LTC. This results in multiple disadvantages for elderly people in rural areas [53] and creates difficulties in meeting both formal and informal care needs.

In addition, the LTC service protection system and LTCI system introduced by the Chinese government may have a potential role in guiding the widening gap between the rich and the poor in LTC service utilization. In Jiangsu province, for example, which is one of the leading economies in China, the LTC service protection system in Jiangsu provides a financial subsidy ranging from 300–800 RMB per month for each elderly person admitted to an LTC institution. However, this is a far cry from the average monthly cost of admission of 3600 RMB for an elderly person in Jiangsu. With this lack of targeted subsidies, the CI of LTC institutionalized seniors in urban areas decreased by 0.07 in 2015 under the service protection policy, while in rural areas it increased by 0.27. That is, urban seniors with generally good social security and rural seniors with good financial conditions are more willing to receive LTC services in institutions. China’s LTCI system, which is being piloted, also shows an imbalance between urban and rural payment capacity. For example, the LTCI pilot in Qingdao includes both urban and rural areas, with urban workers covering 10% of the cost and others covering 20% or 40% [23]. This practice violates the basic requirements of existing research on resource distribution in LTC systems [2] and does not achieve a balance between coverage and welfare. Social security arrangements in China create significant exclusions from service utilization for the poor elderly in rural areas, which is a huge systemic pitfall for LTC resources and healthcare service utilization. People with social security benefits are more likely to be able to afford LTC, and there is a huge disparity in social security benefits between urban and rural areas: 28% of urban seniors with disabilities receive generous benefits, compared to only 5% in rural areas [54]. China thus faces the problem characteristic of low- and middle-income countries of sustaining LTC policies [55], while large differences in the existing systems in urban and rural areas make it difficult to improve the rural LTC situation in the short term.

In addition, the current government subsidies in the Chinese LTC system include both the construction subsidy and operating subsidy. The construction subsidy is based on the number of beds built by the institution at the time of construction. The operating subsidy is based on the actual number of residents. We believe that the large subsidy has been used to support the expansion of facility investment by service production entities in LTC institutions, which is consistent with government practices in other service areas [56]. And yet, given the lack of supporting financial policies to encourage utilization of LTC by economically disadvantaged rural elderly, such as cost sharing of disabled elderly and improvements to service quality. Not only make the treatment of disabled elderly who need to get LTC services not treated better, but also makes them reluctant to stay in the institutions. In China, a large number of rural LTC facilities provide only basic food and housing services to control costs and lack the provision of medical care services. At the same time, some institutions cheat the operating subsidy by attracting self-care elderly (who are not covered by the LTC system) people to stay. Therefore, it’s understandable the expansion of LTC institutions based on policy requirements, particularly but not exclusively in rural areas, has generated a large number of idle beds. This ultimately led to opposite directions of development in the distribution and utilization of LTC resources in urban and rural areas, although they have similar bed resource distribution.

Geographic disparities in healthcare resources are prevalent in most countries and contribute indirectly to the unequal spatial distribution of individual healthcare. The study of the key mechanisms responsible for this phenomenon is an important area of public health research [57]. Analysis of regional differences in resource distribution for LTC services in China has shown that LTC resources are still significantly higher in the Eastern region than in the Central and Western regions, and that bed distribution levels in the Eastern region are already similar to those in Japan and South Korea [42]. On the one hand, this is due to demographic factors such as the density of the elderly population in the Eastern region and the high number of elderly people in need of LTC. On the other hand, in the Eastern region, the economic level is higher and LTC is more market-oriented, with companies more willing to invest there. However, this inequality in resource investment is likely to further aggravate health inequality among the elderly population, perpetuating the spatial pattern of high levels in the Eastern region and low levels in the Central and Western regions in terms of overall health status [58,59].

The results of our study suggest that service utilization is affected not only by economic factors but also by macro policy regulations. We find that resource utilization is indeed higher in the Eastern region than in the Central and Western regions. The reason for this discrepancy may be related to the operating subsidy policies. Apart from the previously mentioned operating subsidy based on the number of residents, the government also provides implicit operating subsidies consisting of tax breaks and institutional water, electricity, and gas cost discounts. However, the central government has not clearly defined the target, scope, and amount of these subsidies. Cities have a relatively large degree of discretion in setting the subsidies. For example, Jiangsu province in the eastern region stipulates that LTC institutions don’t need to pay corporate income tax. At the same time, the institution is allowed to pay for the use of water, electricity, and gas at the civilian standard. In Shanxi Province, located in the central region, institutions are only exempted from 50% of corporate income tax. Meanwhile, in some western provinces, there is no water, electricity, or gas usage fee concession policy. This policy disparity allows the wealthier east to have more policy incentives, which is opposed to the inter-regional pressure to operate LTC. This ultimately leads to higher financial expenses for seniors in the central and western regions to access services, which aggravates the differences in service utilization among regions.

Furthermore, a comparison between the Central and Western regions shows that the number of services per resident in the Western region was higher than in the Central region in 2017, but that the economic situation is lower overall. This finding is inconsistent with earlier studies’ characterization of elderly care services as pro-rich [8]. Adding this finding to our examination of the relevant CI values. We can also confirm that in recent years, with the Chinese government’s policy investment in the Central and Western regions, more and more resources have been concentrated on low-income groups. China has been sharing the LTC costs of older adults in these regions through the government purchase of services to increase their healthcare service utilization and improve their health status. Such macro-level policy interventions may themselves be responsible for disparities in service utilization, as demonstrated in previous studies on health management service utilization among older adults [60].

Based on the findings of this paper, to promote the LTC system as equitable as possible and create an age-friendly society. The government needs to contribute at both ends of resource distribution and support for utilization.

This study analyzes equality in LTC resources and healthcare services utilization in China from 2013 to 2017. Due to changes in the availability of statistics, we were unable to use the most recent data. At the same time, due to the objective lack of data for the four provinces, the sample used in this study is actually based on the territory of mainland China other than these areas and may not be fully representative of the whole country. Nevertheless, developments in the level of equality of disabled residents are obvious, and the Chinese government should release more recent data so that this phenomenon can be better understood. In addition, the discussion of service utilization needs to be more detailed than has been possible in the present study; future work should refine the indicators to explore causal relationships in greater depth, for example by constructing broader indicators of institutional financial inputs or staff salary levels to analyze whether and how LTC services in China are skewed in favor of richer groups. Indicators such as urban–rural geographic space and gender could also be constructed to clarify other factors that impact resource distribution and utilization of LTC services.