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Record W4383198098 · doi:10.3389/fpubh.2023.1150344

Assessing the effect of health status on multidimensional poverty among older adults: the Chinese longitudinal healthy longevity survey

2023· article· en· W4383198098 on OpenAlexaff
Lülin Zhou, Change Zhu, Christine A. Walsh, Xinjie Zhang

Bibliographic record

VenueFrontiers in Public Health · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsUniversity of Calgary
FundersNational Natural Science Foundation of China
KeywordsLongevityGerontologyPovertyLongitudinal studyMedicineHealthy agingDemographyEnvironmental healthSociologyPolitical science

Abstract

fetched live from OpenAlex

Background This study aimed to explore the association between health status (physical, mental, and self-rated health) and multidimensional poverty (subjective and objective poverty) in older adults. Method A panel binary logit regression approach was applied to four waves of CLHLS data (2008, 2011, 2014, and 2018). In total,1,445 individuals were included after data cleaning. Results The mean values and proportion of physical, mental, and self-rated health were 5.73 (87.42%), 0.93 (93.06%), and 3.46 (86.7%), respectively, and mean values and proportion of subjective and objective poverty were 0.19 (18.51%) and 0.21(21.4%). In addition, physical, mental, and self-rated health were all found to be associated with subjective poverty among older adults ( r = −0.181, r = −0.630, r = −0.321, p < 0.05), that is, the better the physical, mental, and self-rated health, the lower the probability of subjective poverty. A comparable connection between self-rated health and objective poverty also exists ( r = −0.157, p < 0.05). Furthermore, medical expenditure played a mediation role in the association between the health status and poverty of older adults. Conclusion In order to effectively alleviate the poverty of older adults, strategies should be taken to improve the health level of older adults, especially the physical and mental health of high-aged older adults, and the self-rated health of middle-aged older adults. Furthermore, social security and pensions should be further developed to adequately reimburse medical expenditures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.070
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.046
GPT teacher head0.316
Teacher spread0.271 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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