Disadvantaged Early-Life Socioeconomic Circumstances Are Associated With Low Respiratory Function in Older Age
Bibliographic record
Abstract
BACKGROUND: Poor lung function in late life may stem from early-life risk factors, but the epidemiological evidence is inconsistent. We investigated whether individuals who experienced disadvantageous socioeconomic circumstances (SEC) in early life showed lower levels of respiratory function in older age, a steeper decline over time, and whether these relationships were explained by adult-life SEC, body mass index, and physical inactivity in older age. METHODS: We used data from the Survey of Health Ageing and Retirement in Europe (2004-2015). Participants' peak expiratory flow (PEF) was assessed with a mini-Wright peak flow meter at second, fourth, and sixth waves. Confounder-adjusted linear mixed-effect models were used to examine the associations between early-life SEC and PEF in older age. A total of 21,734 adults aged 50-96 years (46,264 observations) were included in the analyses. RESULTS: Older adults with disadvantaged early-life SEC showed lower levels of PEF compared with those with advantaged early-life SEC. The association between early-life SEC and late-life PEF persisted after adjusting for adult-life SEC, smoking, physical inactivity, and body mass index. PEF declined with age, but the effect of early-life SEC on this decline was not consistent across robustness and sensitivity analyses. CONCLUSIONS: Early life is a sensitive period for respiratory health. Further considering the effect of SEC arising during this period may improve the prevention of chronic respiratory diseases.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".