Happy life expectancy among older adults: differences by sex and functional limitations
Bibliographic record
Abstract
OBJECTIVE: To evaluate if the happy life expectancy in older adults differs according to sex and functional limitations. METHODS: Life expectancy was estimated by Chiang method, and happy life expectancy was estimated by Sullivan method, combining mortality data with the prevalence of happiness. The questions on happiness and limitations came from a health survey, which interviewed 1,514 non-institutionalized older adults living in the city of Campinas, SP, Southeastern Brazil. The happy life expectancy was estimated by sex, age, and functional limitations. Based on the variance and standard error of the happy life expectancy, we estimated 95% confidence intervals, which allowed us to compare the statistical differences of the number of happy years lived among men and women. RESULTS: Differences by sex in happy life expectancy were significant at ages 60, 65, and 70. In absolute terms, women live more years happily. But, in relative terms, older men could expect to live proportionally more years with happiness. Happy life expectancy decreased significantly with increasing age in both men and women. Among older people living without functional limitation, differences by sex were statistically significant in all age groups, except at age 80. In the group with limitations, no significant differences by sex were found. Significant differences between the group without and with functional limitations were seen in both men and women. CONCLUSIONS: Older men could expect to live a greater proportion of their lives happily in comparison to same-aged women, but women show more years with happiness than men. Functional limitations have a significant impact on happy life expectancy for both sexes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".