Evidence mapPaperPMID 40864628Full record

ArticlePloS one2025

The relationship between social support and physical and mental health in an older male population: Evidence from China Health and Retirement Longitudinal Study (CHARLS).

Yanling Li, Yi Xiang

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Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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

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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

2 citing papers in PubMed.

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4 · The record

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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

2 authors.

Yanling LiSchool of Public Administration and Law, Hunan Agricultural University, Changsha, China.
Yi XiangSchool of Public Administration and Law, Hunan Agricultural University, Changsha, China.ORCID https://orcid.org/0009-0004-9374-5972

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of increasing population aging and decreasing birth rate, it is of great practical significance to explore the impact of social support on the health of elderly men, which is of great practical significance to smoothly promote the strategy of healthy China and actively implement the strategy of population aging. Using the newly released 2020 China Health and Retirement Longitudinal Study (CHARLS) data for a total of 1,510 study participants, this paper analyzes the impact of social support on the health of elderly men using the Oder Probit, OLogit, and PSM models, and then explores the variability across age stages and literacy levels, and eliminates the propensity score matching modeling by endogeneity problems caused by sample selectivity bias. The study shows that social support significantly improves the health of older men in the context of a deepening aging process, showing positive improvements in both self-assessed health and mental health. The robustness test (by replacing the econometric model) further confirmed the reliability of the findings. Heterogeneity tests, on the other hand, revealed significant differences in the impact of social support on the health of male older adults: its health-enhancing effect was more pronounced in less literate male older adults compared to the more literate group. The results of the endogeneity analysis showed that the PSM model effectively mitigated the endogeneity problem of the model. Failure to deal with endogeneity would lead to underestimation of two aspects: first, the health-enhancing effect of social support on self-assessed health of male older adults; and second, its improvement effect on mental health. Therefore, the Chinese government should pay more attention to the key role of social support in improving the health of male older adults, and take diversified and innovative initiatives to focus on enhancing social support in order to more effectively promote the goal of healthy aging.

Indexed as

AgingHealth StatusMental HealthRetirementSocial SupportAgedAged, 80 and overChinaHumansLongitudinal StudiesMaleMiddle Aged

Identifiers

PMID40864628
PMCPMC12385382

What Socratic holds

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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 Socratic graph.