Neighborhood Deprivation, Individual Socioeconomic Status, and Frailty in Older Adults
Bibliographic record
Abstract
OBJECTIVES: To assess how individual socioeconomic status and neighborhood deprivation affect frailty. DESIGN: Nationally representative population-based study, the English Longitudinal Study of Aging (ELSA), analyzed cross-sectionally. PARTICIPANTS: Four thousand eight hundred eighteen individuals aged 65 and older. MEASUREMENTS: Outcome was a frailty index (FI), based on 58 potential deficits, with a theoretical range from 0 to 1; exposures were individual wealth and neighborhood deprivation (lack of local resources, financial and otherwise), based on a set of standard indicators. RESULTS: The FI score varied independently according to wealth and neighborhood deprivation. The mean FI score for an individual in the highest 20% of wealth and least deprived 20% of neighborhoods was 0.09 (95% confidence interval (CI)=0.09-0.09) and for an individual in the lowest 20% of wealth and most deprived 20% of neighborhoods was 0.17 (95% CI=0.16-0.17). CONCLUSION: Frailty in older adults is independently associated with individual and neighborhood socioeconomic factors. Older adults who are poor and live in deprived neighborhoods are most vulnerable. Policies and interventions intended to prevent or reduce frailty must take into account individual circumstances and the broader social settings in which individuals are located.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".