Ventilatory function as a predictor of mortality in lifelong non-smokers: evidence from large British cohort studies
Bibliographic record
Abstract
BACKGROUND: Reduced ventilatory function is an established predictor of all-cause mortality in general population cohorts. We sought to verify this in lifelong non-smokers, among whom confounding by active smoking can be excluded, and investigate associations with circulatory and cancer deaths. METHODS: In UK Biobank, among 149 343 white never-smokers aged 40-69 years at entry, 2401 deaths occurred over a mean of 6.5-year follow-up. In the Health Surveys for England (HSE) 1995, 1996, 2001 and Scottish Health Surveys (SHS) 1998 and 2003 combined, there were 500 deaths among 6579 white never-smokers aged 40-69 years at entry, followed for a mean of 13.9 years. SD (z) scores for forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) were derived using Global Lung Initiative 2012 reference equations. These z-scores were related to deaths from all causes, circulatory disease and cancers using proportional hazards models adjusted for age, sex, height, socioeconomic status, region and survey. RESULTS: In the HSE-SHS data set, decreasing z-scores for FEV1 (zFEV1) and FVC (zFVC) were each associated to a similar degree with increased all-cause mortality (hazard ratios per unit decrement 1.17, 95% CI 1.09 to 1.25 for zFEV1 and 1.19, 95% CI 1.10 to 1.28 for zFVC). This was replicated in Biobank (HRs 1.21, 95% CI 1.17 to 1.26 and 1.24, 1.19 to 1.29, respectively). zFEV1 and zFVC were less strongly associated with mortality from circulatory diseases in HSE-SHS (HR 1.22, 95% CI 1.06 to 1.40 for zFVC) than in Biobank (HR 1.47, 95% CI 1.35 to 1.60 for zFVC). For cancer mortality, HRs were more consistent between cohorts (for zFVC: HRs 1.12, 95% CI 1.01 to 1.24 in HSE-SHS and 1.10, 1.05 to 1.15 in Biobank). The strongest associations were with respiratory mortality (for zFVC: HRs 1.61, 95% CI 1.25 to 2.08 in HSE-SHS and 2.15, 1.77 to 2.61 in Biobank). CONCLUSIONS: Spirometric indices predicted mortality more strongly than systolic blood pressure or body mass index, emphasising the importance of promoting lung health in the general population, even among lifelong non-smokers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".