The association of grip strength with cardiovascular diseases and all-cause mortality in people with hypertension: Findings from the Prospective Urban Rural Epidemiology China Study
Bibliographic record
Abstract
BACKGROUND: Both hypertension and grip strength (GS) are predictors of mortality and cardiovascular disease (CVD), but whether these risk factors interact to affect CVD and all-cause mortality is unknown. This study sought to investigate the associations of GS with the risk of major CVD incidence, CVD mortality, and all-cause mortality in patients with hypertension. METHODS: GS was measured using a Jamar dynamometer (Sammons Preston, Bolingbrook, IL, USA) in participants aged 35-70 years from 12 provinces included in the Prospective Urban Rural Epidemiology China Study. Cox frailty proportional hazards models were used to examine the associations of GS and hypertension and the outcomes of all-cause mortality and CVD incidence/mortality. RESULTS: Among 39,862 participants included in this study, 15,964 reported having hypertension, and 9095 had high GS at baseline. After a median follow-up of 8.9 years (interquartile range, 6.7-9.9 years), 1822 participants developed major CVD, and 1250 deaths occurred (388 as a result of CVD). Compared with normotensive participants with high GS, hypertensive patients with high GS had a higher risk of major CVD incidence (hazard ratio (HR) = 2.39; 95% confidence interval (95%CI): 1.86-3.06; p < 0.001) or CVD mortality (HR = 3.11; 95%CI: 1.59-6.06; p < 0.001) but did not have a significantly increased risk of all-cause mortality (HR = 1.24; 95%CI: 0.92-1.68; p = 0.159). These risks were further increased if hypertensive participants whose GS level was low (major CVD incidence, HR = 3.31, 95%CI: 2.60-4.22, p < 0.001; CVD mortality, HR = 4.99, 95%CI: 2.64-9.43, p < 0.001; and all-cause mortality, HR = 1.93, 95%CI: 1.47-2.53, p < 0.001). CONCLUSION: The present study demonstrates that low GS is associated with the highest risk of major CVD incidence, CVD mortality, and all-cause mortality among hypertensive patients. High levels of GS appear to mitigate long-term mortality risk among hypertensive patients.
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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 | 0.002 | 0.002 |
| 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".