Evidence map›Paper›PMID 36620273›Full record

ArticleFrontiers in public health2022

Spatial-temporal analysis of urban-rural differences in the development of elderly care institutions in China.

Xiang Li, Chen Li, Yi Huang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
14.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Capacity utilization of China's elderly care service industry during 2010-2022.Cost effectiveness and resource allocation : C/E · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Xiang LiSchool of Economics and Management, Sanming University, Sanming, China.
Chen LiSchool of Management, Shanghai University of Engineering Science, Shanghai, China.
Yi HuangSchool of Geographic Sciences, Nantong University, Nantong, China.
Nantong University · CNSanming University · CNShanghai University of Engineering Science · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Aging is both a sign of rising life expectancy per capita and social progress, and a challenge for society. Due to the decline in physiological functions, the rate of illness has increased significantly, leading to a rise in demand for healthcare, life care and other elderly care. With the overlapping impact of an aging population, advanced aging, empty nesting families and the weakening of traditional elderly care functions, the issue of elderly care for the empty nesters, the elderly alone and the disabled has become more prominent and has become a focal point of concern for all sectors of society. As an important supplement to the elderly care service system, institutional care, together with home care, community care and rural care, are mutually complementary. Methods: The study establishes a panel database of urban and rural elderly-care institutions in 276 cities from 2010 to 2016, and uses comprehensive measurements to reveal the spatial-temporal changes of urban and rural elderly care institutions in China. Results: First, in terms of spatial pattern, the overall score of elderly care institutions in urban areas shows a "double-high" spatial pattern of higher scores in coastal areas than inland areas, and higher scores in urban areas than in rural areas. In terms of the differences in the scores of secondary indicators, the eastern urban areas have higher scores than the rural areas for the indicators of facilities construction and nursing staff of elderly institutions, while the eastern rural areas have higher scores than their urban counterparts for the indicators of service recipients of elderly institutions. Second, in terms of temporal change, there is a clear "urban progress and rural regression" in the evolution of China's elderly care institutions. Third, in terms of spatial and temporal evolution, there is a clear spatial autocorrelation in the composite scores of urban and rural elderly care institutions in China, and the spatial autocorrelation of the composite scores of elderly care institutions shows a clustering pattern. Discussion: The contradiction between the limited ability to pay of the elderly people staying in elderly care institutions and the huge demand for elderly care services is bound to affect the sustainability of the development of public elderly care institutions in both urban and rural areas. Due to historical factors, the marketisation of elderly care institutions in China started late and the marketisation of elderly care is not high. As the population ages, China's elderly-care institutions have begun to transform from public institutions of a welfare nature to those with some market mechanisms, but the overall transformation has been slow, resulting in the service guarantee system of elderly-care institutions lagging far behind the actual needs of the elderly. The long-term development of elderly care institutions must introduce market mechanisms, enhance the endogenous dynamics of elderly care institutions, correctly handle the relationship between fairness and efficiency of elderly care services, and improve the professionalism, income and treatment of elderly care staff while compensating for the lack of development of elderly care institutions and the inadequate layout of space, so as to continuously improve the service quality of elderly care institutions.

Indexed as

Life ExpectancyRural PopulationAgedChinaHumansPopulation DynamicsSpatio-Temporal AnalysisChinaelderly care institutionslocal spatial autocorrelationspatial-temporal analysisurban-rural differences

Identifiers

PMID36620273
PMCPMC9815020
OpenAlexW4312187126

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.