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Record W4386640336 · doi:10.5539/gjhs.v15n10p1

Trends of Health and Dietary Disparities by Economic Status among Elderly Individuals in Japan from 2004 to 2014: A Repeated Cross-Sectional Survey

2023· article· en· W4386640336 on OpenAlexvenueno aff
Daisuke Machida

Bibliographic record

VenueGlobal Journal of Health Science · 2023
Typearticle
Languageen
FieldNursing
TopicNutrition, Health and Food Behavior
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsCross-sectional studyLogistic regressionMedicineGerontologyEnvironmental healthLife satisfactionMealSocioeconomic statusDemographyPsychologySocial psychology

Abstract

fetched live from OpenAlex

This study examines the changes in health and dietary disparities by economic status among elderly individuals in Japan from 2004 to 2014. The study design utilized a repeated cross-sectional approach, using data from the Survey of Attitudes among the Elderly toward Daily Life in 2004 and 2014. Logistic regression analysis was performed with subjective economic status, survey year, and their interactions as independent variables, and self-rated health, dietary satisfaction, and intake of balanced meals as dependent variables. The results revealed that disparities in self-rated health, dietary satisfaction, and intake of a balanced meal were present due to economic status. Furthermore, the disparities in self-rated health, dietary satisfaction, and balanced meal intake by economic status remained unchanged from 2004 to 2014 (P for interaction ≥ 0.05). The findings were consistent in sensitivity analyses conducted on those aged 75 and older, as well as on long-term care insurance recipients.

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)0.005
metaresearch head score (Gemma)0.000
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 score0.046
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.379
Teacher spread0.333 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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