Factors across life associated with remaining free from functional limitations despite lifelong exposure to socioeconomic adversity
Bibliographic record
Abstract
BACKGROUND: There are substantial socioeconomic inequalities in functional limitations in old age. Resilience may offer new insights into these inequalities by identifying constellations of factors that protect some individuals from developing functional limitations despite socioeconomic adversity. METHODS: Data from 1973 participants in the Medical Research Council National Survey of Health and Development (Great Britain), followed from birth until age 60-64, were used. Functional limitations were defined as reporting difficulty with at least 1 of 16 activities at age 60-64. Lifetime socioeconomic adversity was based on socioeconomic trajectories, categorised into three adversity levels. Analysis of covariance and regression models were used to compare psychosocial factors and health-related behaviours between a 'Resilient' group (high adversity but no functional limitations) and five groups with other combinations of adversity and limitations. RESULTS: Prevalence of functional limitations in high, intermediate and low adversity groups was 44%, 30% and 23% in men, and 61%, 55% and 49% in women, respectively. Compared with the other high adversity group, the resilient group had a lower prevalence of childhood illness (12% vs 19%) and obesity throughout ages 43-64 (70% vs 55%). Partially adjusted models also showed higher adolescent self-management, lower neuroticism, higher prevalence of volunteer work and physical activity (age 60-64) and lower prevalence of smoking (age 43) in the resilient. Marital status and contact frequency were not associated with resilience. CONCLUSION: Results suggest protection against childhood illness, health-behavioural factors and self-regulation as targets for interventions across life that may particularly benefit those with long-term exposure to socioeconomic adversity.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".