Time Perspective and All-Cause Mortality: Evidence From the English Longitudinal Study of Ageing
Bibliographic record
Abstract
BACKGROUND: Long-term future thinking has been associated with a range of favorable health behaviors. However, it is currently unclear whether this translates into an effect on morbidity and mortality. PURPOSE: The goal of this study was to study the relationship between time perspective and all-cause mortality and to examine the role of health behavior in explaining this association. METHODS: Participants (N = 9,949) aged 50 and over from the English Longitudinal Study of Ageing, a representative cohort of older English adults, estimated the length of their time horizon for financial planning (time perspective). Two thousand ninety-two deaths were recorded over a 9-year follow-up period (2002/2003-2012). Smoking, physical activity, and alcohol consumption were examined as factors that may underlie the time perspective-mortality link. RESULTS: Our prospective survival analyses showed that those who tend to plan for longer periods experienced a significantly reduced risk of all-cause mortality (HR = 0.83; 95% confidence interval [CI]: [0.80, 0.87], p < .001 per 1 SD increase in future time perspective). This association remained after adjusting for baseline socioeconomic status and health (HR = 0.92; 95% CI: [0.88, 0.97], p < .001). The link between time perspective and mortality was observed across the gradient of financial circumstances and did not appear to be due to reverse causality. Healthy behavior among the more future orientated explained 34% of the link between time perspective and mortality. CONCLUSIONS: Using a simply administered indicator of time perspective, this study suggests that a future-orientated time perspective may be an important predictor of reduced risk of death.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".