Self-Rated Health Predicts Mortality in Very Old Men—the Manitoba Follow-Up Study
Bibliographic record
Abstract
BACKGROUND: Self-rated health (SRH) predicts death, but there are few studies over long-time horizons that are able to explore the effect age may have on the relationship between SRH and mortality. OBJECTIVES: 1. To determine how SRH evolves over 20 years; and 2. To determine if SRH predicts death in very old men. METHODS: We analyzed a prospective cohort study of men who were fit for air crew training in the Second World War. In 1996, a regular questionnaire was administered to the 1,779 surviving participants. SRH was elicited with a 5-point Likert Scale with the categories: excellent, very good, good, fair and poor/bad. We examined the age-specific distribution of SRH in these categories from the age of 75 to 95 years, to the end of the follow-up period in 2018. We constructed age-specific Cox proportional hazard models with an outcome of time to death. RESULTS: SRH declined with age. The gradient in risk of death persisted across all ages; those with poor/fair/bad SRH had consistently higher mortality rates. However, the discrimination between good and excellent was less in those aged 85+. CONCLUSIONS: SRH declines with advancing age, but continues to predict death in older men.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".