Physiological measures variability and risks of heart disease and stroke: evidence from three cohort studies
Bibliographic record
Abstract
BACKGROUND: The overall effect of long-term variability in physiological measures on cardiovascular health of older adults and the underlying mechanic pathway remain uncertain. METHODS: We constructed a composite score (0 ~ 3) of variability in physiological measures, including blood pressure, pulse rate, and body mass index, in older adults from the China Health and Retirement Longitudinal Study (CHARLS) 2011 ~ 2015, the Health and Retirement Study (HRS) 2006/2008 ~ 2014/2016, and the UK Biobank 2006 ~ 2019. The associations of the composite score with incident risks of heart disease and stroke were assessed. The mediation roles of several biomarkers were explored. RESULTS: A higher composite score was related to increased incident risk of heart disease in older adults from the US and the UK and increased incident risk of stroke in all three cohorts. Upon pooling the results, each 1-point increment in the composite score was associated with a 19% (hazard ratio: 1.19; 95% confidence interval: 1.14, 1.30) and a 23% (1.23; 1.12, 1.35) increments in incident risks of heart disease and stroke, respectively. The composite score also exhibited an inverse relationship with grip strength while displaying positive associations with C-reactive protein, glycosylated hemoglobin Alc (HbAlc), and cystatin C. Reduced grip strength, elevated HbAlc, and elevated cystatin C significantly mediated the composite score-associated elevated risks of heart disease and stroke. CONCLUSIONS: Long-term variability in physiological measures was associated with increased incident risks of heart disease and stroke, and the associations were partially mediated through deteriorated biomarkers of muscle strength, hyperglycemia, and kidney function.
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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 | 0.003 |
| 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 | 0.001 |
| 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".