Decomposing the effects of physical activity and cardiorespiratory fitness on mortality
Bibliographic record
Abstract
Characterizing the effects of physical activity (PA) and cardiorespiratory fitness (CRF) on mortality is challenging because the causal relationship between PA, CRF, and other cardiovascular risk factors is unclear. To better understand the effects of PA and CRF on mortality, we re-analyzed data from 42,373 participants in the Aerobics Center Longitudinal Study (ACLS) using a modified version of VanderWeele's four-way causal effect decomposition method. The method was applied to decompose the causal effects of PA and CRF on median time to death into parts reflecting mediation, interaction, mediated interaction, and neither interaction nor mediation. We found that 67% of the effect of PA on mortality was mediated by CRF, while the effect of CRF was not significantly mediated by PA. The effects of both PA and CRF were mediated to a small extent by hypertension and diabetes. There were no meaningful interactions. Our findings strengthen the evidence that the benefit on mortality from PA is largely mediated by its effect on CRF, and support efforts to increase longevity by encouraging PA.
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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".