Evidence map›Paper›PMID 32197415›Full record

ArticleInternational journal of environmental research and public health2020

The Impact of Social Support on the Health of the Rural Elderly in China.

Yunli Bai, Fang Bian, Linxiu Zhang, Yueming Cao

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

56 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

4 authors.

Yunli BaiKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.ORCID 0000-0003-0197-7238
Fang BianCapital Airport Sub-district Office, Chaoyang District, Beijing 100621, China.
Linxiu ZhangKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
Yueming CaoKey Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the dramatic trend of global aging, the physical and mental health of the rural elderly has attracted significant attention. Social support plays an important role in improving the health of the elderly. However, assessing the impact of social support on the physical and mental health of the elderly is challenging in rural China. This paper analyzes the impact of social support on the physical and mental health of the Chinese rural elderly based on data collected from households and village cadres. Probit, Oprobit, and ordinary least squares (OLS) are used to estimate these effects. The results show that 24.3% of the rural elderly are in bad physical health, and 32.9% of them are depressed. Physical and mental health is worse among the female elderly and among those who are in western provinces. Having pensions, taking care of grandchildren, and communicating with children by telephone are shown to significantly improve the mental health of the rural elderly. The government could promote the mental health of the rural elderly by improving public health services, increasing pensions, providing free mobile phones to elderly people in poverty, and advocating that the younger generation provide emotional support.

Indexed as

Mental HealthRural PopulationSocial SupportAgedChildChinaFamilyFemaleHumansPovertyChinadepressionphysical healthrural elderlysocial support

Identifiers

PMID32197415
PMCPMC7143868

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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.