Relationship between Economic Security and Self-Rated Health in Elderly Japanese Residents Living Alone
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to assess the relationship between economic security and self-rated health for elderly Japanese residents living alone. DESIGN: A secondary analysis of a cross-sectional study. SETTING: N City, H. Prefecture, Japan. PARTICIPANTS: Survey questionnaires were distributed to 2,985 elderly residents living alone, aged ≥70 years, of which, 1,939 (65.0%) were returned and treated as valid responses. MEASUREMENTS: The survey included questions about gender, age, number of years spent in N City, self-rated health, economic security, number of years spent living alone, reason for living alone, life satisfaction, cooking frequency, frequency of seeing a doctor, long-term care service usage, as well as whether they enjoyed their lives, participated in social organizations. RESULTS: Of the respondents, 1,563 (80.6%) reported that they were economically secure, and 376 (19.4%) responded that they were insecure. The odds ratio predicting poor self-rated health for the economically insecure participants was significantly high (odds ratio: 3.19, 95%, Confidence Interval (CI): 2.53-4.02, and P < 0.001). Similarly, the adjusted odds ratio for poor self-rated health was significantly high for the economically insecure participants in multivariate analyses controlling for factors such as age, gender, cooking frequency, and social participation (adjusted odds ratio: 2.21, 95%, CI: 1.70-2.88, and P < 0.001). Furthermore, a similar trend was observed in stratified analyses based on gender and age groups. CONCLUSION: Economic security predicted self-rated health independently of confounders, including social participation and cooking frequency, among the elderly Japanese living alone in communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".