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Record W3206526966 · doi:10.1186/s12939-021-01542-y

Does social capital interact with economic hardships in influencing older adults’ health? A study from China

2021· article· en· W3206526966 on OpenAlexaff
Lijuan Gu, Yang Cheng, David R. Phillips, Mark W. Rosenberg, Linsheng Yang, Li Wang, Hairong Li

Bibliographic record

VenueInternational Journal for Equity in Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsQueen's University
FundersYoung Scientists FundPeking UniversityLingnan UniversityChina Postdoctoral Science FoundationPostdoctoral Research Foundation of ChinaNational Natural Science Foundation of China
KeywordsMental healthSocial capitalPsychosocialSocial determinants of healthPovertyPsychologyHealth equitySocial supportPublic healthGerontologyEconomic growthSociologyMedicineSocial psychologyHealth carePsychiatryEconomicsSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: The importance of social and economic capital as predictors of health is widely documented, yet the complexity of interactions between them and effects on older people's health is still unclear. Combining the material and psychosocial explanations of health, this study explores the potential interactions between social and economic capital in influencing older adults' health in urban and rural China. METHODS: Using data from the China Family Panel Survey, physical and mental health in 2018 were regressed on social and economic capital indicators in 2016, controlling for sociodemographic characteristics of 3535 respondents aged 65 and older. Rothman's synergy index was calculated to investigate potential interaction effects. RESULTS: Economic hardships were significantly related to both self-reported health and mental health. Neighborhood cohesion and social participation were significantly associated with mental health for all, bonding trust was significantly associated with mental health for urban older people. We found no significant associations between social capital components and self-reported health. There was an interaction effect between low neighborhood cohesion and economic hardships, and between low social participation and economic hardships, creating an increased burden of poor mental health. The interaction effect between low bonding trust and economic hardships on mental health was apparent only among urban older people. CONCLUSIONS: Geographical settings are important factors in the complexity between social and economic capital in affecting older health. Intervention efforts directed towards reducing simultaneously multiple dimensions of deprivation, such as poverty, social exclusion, social isolation, could be helpful in improving older people's health. In materially deprived places, policies to promote health equity by improving social capital but without eliminating poverty may be less effective.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.462
Teacher spread0.410 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations13
Published2021
Admission routes1
Has abstractyes

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