Evidence map›Paper›PMID 34395373›Full record

ArticleFrontiers in public health2021

Do Social Pension Schemes Promote the Mental Health of Rural Middle-Aged and Old Residents? Evidence From China.

Guochen Pan, Shaobin Li, Zhixiang Geng, Kai Zhan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
3.1field-weighted citation impact, top 7% 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

21 citing papers in PubMed, 40 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Guochen PanDepartment of Insurance and Actuarial Science, Economics and Management School, Wuhan University, Wuhan, China.
Shaobin LiDepartment of Insurance and Actuarial Science, Economics and Management School, Wuhan University, Wuhan, China.
Zhixiang GengDepartment of Insurance and Actuarial Science, Economics and Management School, Wuhan University, Wuhan, China.
Kai ZhanDepartment of Risk Management and Insurance, School of Finance, Guangdong University of Foreign Studies, Guangzhou, China.
Wuhan University · CNGuangdong University of Foreign Studies · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As China experiences rapid aging, the mental health of older rural adults has become a major public health concern. Among other social insurance programs, the New Rural Social Pension (NRSP) scheme was established to replace part of the income for old-age rural residents in China. This article employs survey data from the China Health and Retirement Longitudinal Study (CHARLS) in 2015 and 2018 to investigate the impact of a pension on depression in middle-aged and old residents. Our results show that the pension scheme not only reduces the depressive symptoms of the rural residents but keeps down the prevalence rate of depression. Among the subscribers of the pension scheme, the pensioners benefit more from enrolling in the pension scheme than the contributors in terms of depression alleviation. The impact of pension on depression displays heterogeneity; female residents, residents in central China, and/or those from lower income households are found to be positively affected. It is also confirmed that a pension scheme contributes to easing depression via reduced labor supply, better family support, and more consumption expenditure.

Indexed as

Mental HealthPensionsAdultChinaFemaleHumansLongitudinal StudiesMiddle AgedRural Populationdepressionmental healthnew rural social pensionrural residentsurban-rural resident social pension

Identifiers

PMID34395373
PMCPMC8358066
OpenAlexW3187265378

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.