Effect of Health Protective Factors on Health Deficit Accumulation and Mortality Risk in Older Adults in the Beijing Longitudinal Study of Aging
Bibliographic record
Abstract
OBJECTIVES: To evaluate transitions in health status and risk of death in older adults in relation to baseline health deficits and protective factors. DESIGN: Prospective cohort study with reassessments at 5, 8, and 15 years. SETTING: Secondary analysis of data from the Beijing Longitudinal Study on Aging. PARTICIPANTS: Urban and rural community-dwelling people aged 55 and older at baseline (n = 3,275), followed from 1992 to 2007, during which time 51% died. MEASUREMENTS: Health status was quantified using the deficit accumulation-based frailty index (FI), constructed from 30 intrinsic health measures. A protection index was constructed using 14 extrinsic items (e.g., exercise, education). The probabilities of health changes, including death, were evaluated using a multistate transition model. RESULTS: Women had more health deficits (mean baseline FI 0.13 ± 0.11) than did men (mean baseline FI 0.11 ± 0.10). Although health declined on average (mean FIs increased), improvement and stability were common. Baseline health significantly affected health transitions and survival over various follow-up durations (odds ratio (OR) = 1.27, 95% confidence interval (CI) = 1.17-1.37 for men; OR = 1.24, 95% CI = 1.16-1.33 for women for each increment of deficits). Each protective factor reduced the risk of health decline and the risk of death in men and women by 13% to 25%. CONCLUSION: Deficit accumulation-based transition modeling demonstrates persisting effects of baseline health status on age-related health outcomes. Some mitigation by protective factors can be demonstrated, suggesting that improving physical and social conditions might be beneficial.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".