Accelerated Aging Mediates the Associations of Unhealthy Lifestyles with Cardiovascular Disease, Cancer, and Mortality: Two Large Prospective Cohort Studies
Bibliographic record
Abstract
Abstract With a well-validated aging measure – Phenotypic Age Acceleration (PhenoAgeAccel), this study examined whether and to what extent aging mediates the associations of unhealthy lifestyles with adverse health outcomes. Data were from 405,944 adults (40-69 years) from UK Biobank (UKB) and 9,972 adults (20-84 years) from US National Health and Nutrition Examination Surveys (NHANES). The mediation proportion of PhenoAgeAccel in associations of unhealthy lifestyles with incident cardiovascular disease, incident cancer, and all-cause mortality were 20.0%, 17.8%, and 26.6% (P values <0.001) in UKB, respectively. The mediation proportion of PhenoAgeAccel in associations of lifestyles with cancer mortality, and all-cause mortality were 25.7%, and 35.2% (P values <0.05) in NHANES, respectively. This study demonstrated that accelerated aging partially mediated the associations of lifestyles with adverse health outcomes in UK and US populations. The findings reveal a novel pathway and the potential of geroprotective programs in mitigating health inequality in late-life beyond lifestyle interventions.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".