Frailty Index as a Measure of Biological Age in a Chinese Population
Bibliographic record
Abstract
BACKGROUND: The concept of a frailty index, developed in Canadian elderly populations as an indicator of biological age as opposed to chronological age, was tested in an elderly Chinese population to determine whether it is applicable in a different ethnic and cultural setting. METHODS: A data set including 62 physical, psychological, and socioeconomic variables from a cohort of 2,032 persons 70 years and older (999 men, 1,033 women) was used. The distribution of the index was evaluated using the Cramer-von Mises goodness-of-fit test, and multiple linear regression was used to assess its relationship with age and sex. A biological age for each participant was calculated based on an inverse regression of age on mean frailty index and sex. The Cox proportional hazards regression model was used to assess the ability of biological age to predict death. RESULTS: The distribution of the frailty index most closely resembled a Weibull distribution. The frailty index increased with age until the mid-80s, when it leveled off, and was higher in women than men for each age group. The distribution of biological age is wider than that for chronological age, and it strongly predicted death. Women had an estimated 20% lesser chance of dying at a given time than did men of the same chronological age and degree of frailty. CONCLUSIONS: The study confirms the robustness of the concept and method of calculating the frailty index developed in elderly Canadian populations. It also suggests that the sex difference in life expectancy may have an underlying genetic basis independent of frailty.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".