Early-life socioeconomic position and the accumulation of health-related deficits by midlife in the 1958 British birth cohort study
Bibliographic record
Abstract
Abstract Reducing population levels of frailty is an important goal and preventing its development in mid-adulthood could be pivotal. Childhood socioeconomic position (SEP) is associated with a myriad of adult health outcomes but evidence is limited on associations with frailty. Using 1958 British birth cohort data (N=8711), we aimed to: (i) establish the utility of measuring frailty in mid-life, by examining associations between a 34-item frailty index at 50y (FI 50y ) and mortality over an eight-year follow-up period and (ii) examine associations between early-life SEP and FI 50y and investigate whether these associations were explained by adult SEP. Hazard ratios (HRs) for mortality increased with increasing levels of frailty, e.g., HR sex-adjusted was 4.07(95% CI:2.64,6.25) for highest vs. lowest fifth of FI 50y . Lower early-life SEP was associated with higher FI 50y : per unit decrease in early-life SEP (on a 4-point scale), FI 50y increased by 12.7%(10.85%,14.6%) in a model adjusted for early-life covariates. After additional adjustment for adult occupational class and education, the association attenuated to 5.71%(3.71%,7.70%). Findings suggest that early-life SEP is associated with frailty and that adult SEP only partially explains this association. Results highlight the importance of improving socioeconomic circumstances across the life course to reduce inequalities in frailty from mid-adulthood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".