Employment in old age and all‐cause mortality: A systematic review
Bibliographic record
Abstract
Social participation promotes and maintains the health of older adults. Working is a type of social participation; however, the effect of employment in old age on health outcomes has not been established. This study aimed to review the relationship between employment in old age (≥60 years) and all-cause mortality. For this systematic review, a computerized search was performed using PubMed, CINAHL and PsycINFO for prospective studies published through June 2020. The observational studies were extracted according to the study participants, indicators, follow-up period, statistical approach and main results. The quality of the studies was assessed using the Newcastle-Ottawa Scale. Of the 37 832 records identified, 14 studies were included in the systematic review based on the inclusion and exclusion criteria. Eight studies were derived from Asian countries (four from Japan, two from Taiwan and one from Thailand and South Korea), three were from the United States, two were from Israel and one was from Brazil. The baseline data of 13 studies were collected before 2000. Thirteen of the 14 studies reported any association between employment in later life and a lower risk of mortality. Four studies examined the sex-related differences in the effect of later-life employment on all-cause mortality, but the association was controversial. Overall, we revealed that working in old age would lower mortality risk. Although more findings based on recent data are required, this study indicates that working later in life is beneficial for promoting and maintaining health. Geriatr Gerontol Int 2022; 22: 705-714.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".