Gender differences in healthy life expectancy among Brazilian elderly
Bibliographic record
Abstract
BACKGROUND: This study examined gender differences in healthy life expectancy (HLE) and unhealthy life expectancy (UHLE) among people aged 60 years or older living in a large Brazilian city. METHODS: Based on Chiang method, abridged life tables were constructed for men and for women. To calculate HLE, the Sullivan method was applied. Estimates of the prevalence of self-rated health and self-reported functional disability (global, mild/moderate, and severe) were obtained from a population-based household survey carried out in 2008, which involved non-institutionalized individuals. RESULTS: Findings showed that women live longer and these extra years would be spent in good self-rated health. For example, women aged 60 would live, on average, 4 more years in good health in comparison to men. In terms of global limitations and mild/moderate limitations, no gender differences were detected for HLE. However, UHLE was statistically higher among women than among men at all ages in the global limitations and mild/moderate limitations (except for the age 80). Women at age 60, for instance, could expect to live 3.1 years longer with mild/moderate limitations compared to men. Gender differences were identified for severe limitations for either HLE or UHLE. In comparison to men, women at age 60, for example, would expect to live 2.5 and 2.0 more years without and with severe limitations. CONCLUSIONS: By showing that the advantage of longer life expectancy among women is not necessarily accompanied by worse health conditions, these findings add some evidence to the debate about male-female health-survival paradox. Policy efforts are necessary to reduce gender differences in the quantity and quality of years to be lived, providing equal opportunities to women and men live longer with quality of life, autonomy, and independence.
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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 | 0.000 |
| 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 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".