Determining the spatial distribution of nursing homes in China: a spatial heterogeneity analysis

Zhang, Bo; He, Shixiong; Chen, Xingyu; Jiang, Lei

doi:10.1007/s10901-021-09908-y

Cited by 4 publications

(6 citation statements)

References 24 publications

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“…In contrast, a comparison with the United States reveals that physicians in the US are inclined to gravitate towards areas with higher income, unlike in Japan where such a pattern is absent; these distinguishing features are attributed to the existence of public health insurance in Japan [13][14]. In addition, China, which has a demography characterized by rapid aging similar to that of Japan, exhibits regional variability in nursing homes and disparities in the diversity of facilities around the elderly [15][16].…”

Section: Previous Researchmentioning

confidence: 92%

“…Although these two studies provide some perspective on the structure Data Analysis Initially, we aimed to identify the associated structure of the distribution of medical and care resources in the 334 SMAs nationwide. To formulate a hypothesis about this related structure, an exploratory factor analysis (EFA) using the variables in Table 2 regarding medical and care resources was performed 15 . The number of factors was determined from a parallel analysis, and promax rotation was used in the EFA for the purpose of making the interpretation of the solution realistic and easy.…”

Section: Previous Researchmentioning

confidence: 99%

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The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

Kusunoki

Yoshikawa

2023

Preprint

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Background Given Japan’s rapidly aging population, a coordinated system for providing medical and care services tailored to regional characteristics needs to be established. To gain useful knowledge for the development of such a system, the present study aimed to identify the structure of the distribution of medical and care resources based on regional characteristics. Methods Initially, regional characteristics were used to group all 334 secondary medical areas in Japan by principal component analysis. Subsequently, the related structure of the distribution of medical and care resources was modeled using structural equation modeling. Finally, multigroup analysis was conducted to investigate differences in the models across groups. Results The nationwide secondary medical areas were categorized based on urbanicity and low-density urbanicity, which revealed differences in the related structure of the distribution of medical and care resources. Conclusions The key finding was that the government’s objective of reducing hospital beds to enhance medical delivery efficiency may not be achieved solely by expanding nursing homes. This finding was particularly relevant in low-density urbanicity groups. Given concerns about the oversupply of nursing homes and sprawl in such areas, we conclude that trends in the location of nursing homes should be closely monitored.

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Section: Previous Researchmentioning

confidence: 92%

Section: Previous Researchmentioning

confidence: 99%

The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

Kusunoki

Yoshikawa

2023

Preprint

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“…There is no uniform index system of elder care resources in the literature. According to the core connotation of resources, the most basic elements are material resources, human resources and financial resources [ 27 , 51 ]. This study constructs a quantitative indicator system to measure the level of SECR, which consists of material resources, human resources and financial resources provided by the subjects outside the family for the elderly.…”

Section: Index System For Measuring the Level Of Secrmentioning

confidence: 99%

“…The existing literature contribute to evaluating the supply–demand matching [ 37 ], the suitability [ 19 ], regional disparities [ 47 ] and sustainability [ 28 , 50 ] of the elderly care service facilities. Coupling coordination coefficient and deviation degree index method was used to explore the matching relationship between the elderly care resources and the elderly population in China [ 27 , 51 ]. Due to the impact of population size, structure and distribution on the existing allocation of public care resources, there are some issues in SECR allocation, such as insufficient effective supply [ 15 , 46 ], uneven resource allocation between regions [ 22 , 25 ], and a mismatch between service facilities and the elderly population [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal evolution and influencing factors of the allocation of social care resources for the older adults in China

Peng,

Huang,

Deng

2023

Int J Equity Health

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Background The reasonable allocation of social care resources for the older adults is a key measure to actively respond to population aging. This study aims to evaluate the evolutionary trend, spatial differences and influencing factors of the social elderly care resources (SECR) allocation in China. Methods This study constructed a comprehensive index system consisting of three dimensions: material resources, human resources and financial resources, to measure the level of SECR in mainland China. The Kernel density estimation was used to reveal the dynamic evolution trend, and Dagum Gini Coefficient and its decomposition method were used to investigate the equity of SECR allocation. Spatial panel regression models were used to analyze the influencing factors of the allocation of SECR. Results The level of SECR is rising from 0.197 in 2013 to 0.208 in 2019. The middle-high- and high-level areas of SECR were mainly distributed in the eastern and western China. The Gini coefficient of SECR decreased from 0.262 in 2013 to 0.249 in 2019. Per capita GDP, the proportion of social welfare expenditure in GDP and the proportion of the tertiary industry in GDP have significant positive effects on the allocation of SECR. Population aging and the development of service industry exhibit significant negative spatial spillover effects on the allocation of SECR. Conclusions The fairness of the allocation of SECR in China has been improved, while the spatial distribution is imbalanced. Economic development, fiscal input and the development of service industry have significant positive effects while population aging has significant negative effects on the SECR allocation.

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“…By contrast, a comparison with the USA reveals that physicians in the USA are inclined to gravitate toward areas with higher income, unlike in Japan, where no such pattern is seen; these distinguishing features are attributed to the existence of universal public health insurance in Japan [ 11 , 12 ]. In addition, China exhibits regional variability in nursing homes and disparities in the diversity of facilities around the aged [ 13 , 14 ]. Nevertheless, these studies are confined to analyzing medical and care resources in isolation, and thus, the relationship between the two resources remains poorly understood.…”

Section: Introductionmentioning

confidence: 99%

The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

Kusunoki,

Yoshikawa

2024

BMC Health Serv Res

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Background Given Japan’s rapidly aging population, the Ministry of Health, Labour and Welfare's policy of reducing hospital beds and replacing medical care with nursing care requires the establishment of a coordinated system of medical and care services tailored to regional characteristics. To gain useful knowledge for the development of such a system, this study aimed to identify differences in the structure of the relationship between medical and care resources due to differences in regional characteristics. Methods Initially, regional characteristics were used to group all 334 secondary medical areas (SMA) in Japan by principal component analysis. Subsequently, the related structure of the distribution of medical and care resources for each group were compared. For these　comparisons, first, the related structure of the distribution of medical and care resources nationwide was modeled using structural equation modeling. Secondly, multigroup analysis was conducted to investigate differences among the models across groups. Results The nationwide SMAs were grouped largely based on urbanicity and middle-density regionality. The groups with high urbanicity and high middle-density regionality consisted of SMAs with a high and medium population density. By contrast, the low middle-density regionality group consisted of SMAs containing large cities with a high population density and depopulated areas with a low population density. The model of the related structure of the distribution of medical and care resources differed among these groups. In the non-urbanicity and middle-density regionality groups, nursing care abundance tended to increase acute care abundance. In addition, in all groups, nursing care abundance tended to increase long-term hospitalization care abundance and clinic care abundance (with beds). Conclusions The key finding of this study was that the government’s objective of reducing hospital beds may not be achieved solely by expanding nursing homes. This is because many of the models did not show a tendency that higher nursing care abundance reduces the values of the factors which increase more hospital beds. This finding was particularly relevant in middle-density regionality groups. This finding suggests that the location of nursing homes should be monitored because of concerns about the oversupply of nursing homes and sprawl in those areas.

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Determining the spatial distribution of nursing homes in China: a spatial heterogeneity analysis

Cited by 4 publications

References 24 publications

The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

Spatiotemporal evolution and influencing factors of the allocation of social care resources for the older adults in China

The distribution structure of medical and care resources based on regional characteristics throughout Japan in 2020

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