And mortality in older Chinese adults: Results from the Beijing longitudinal study of aging
Bibliographic record
Abstract
OBJECTIVES: Falls are well known to be associated with adverse health outcomes, especially when complicated by fracture. Falls are more common in people who are frail and readily related to several items in the frailty phenotype. Less is known about the relationship between falls and frailty defined as deficit accumulation. Our objective was to investigate the relationship between falls, fractures, and frailty based on deficit accumulation. DESIGN: Representative cohort study, with 8 year follow-up. SETTING: The Beijing Longitudinal Study of Aging (BLSA). PARTICIPANTS: 3,257 Chinese people aged 55+ years at baseline. MEASUREMENTS: A frailty index (FI) was constructed using 33 health deficits, but excluding falls and fractures. The rates of falls, fractures and death as a function of age and the FI were analyzed. Multivariable models evaluated the relationships between frailty and the risk of recurrent falls, fractures, and mortality adjusting for age, sex, and education. Self or informant reported fall and fracture data were verified against participants' health records. RESULTS: Of 3,257 participants at baseline (1992), 360 people (11.1%) reported a history of falls, and 238 (7.3%) reported fractures. By eight years, 1,155 people had died (35.3%). The FI was associated with an increased risk of recurrent falls (OR=1.54; 95% confidence interval (CI)=1.34-1.76), fractures (OR=1.07; 95% CI=0.94-1.22), and death (OR=1.50, 95% CI=1.41-1.60). The FI showed a significant effect on mortality in a multivariate Cox regression model (Hazard Rate=1.29, 95% CI=1.25-1.33). When adjusted for the FI, neither falls nor fractures were associated with mortality. CONCLUSION: Falls and fractures were common in older Chinese adults, and associated with frailty. Only frailty was independently associated with death.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".