Association of sitting time with cardiovascular events among manual and non-manual workers: a prospective cohort study (PURE-China)
Bibliographic record
Abstract
BACKGROUND: Prolonged sitting time is associated with an increased risk of cardiovascular disease (CVD) in the general population. However, it is unclear how these risks differ across occupational groups. This study aimed to investigate the association between sitting time and CVD in manual and non-manual workers among Chinese adults. METHODS: This population-based cohort study recruited 47,931 participants aged 35 to 70 years from 115 communities across 12 provinces in China between 2005 and 2009. Daily sitting time was measured using the International Physical Activity Questionnaire (IPAQ). The main outcome was a major CVD event (defined as cardiovascular death, myocardial infarction, stroke, or heart failure). Information on each participant's occupation was collected using standardized questionnaires and categorized into manual and non-manual occupations according to the Italian National Institute of Statistics 2001 (ISTAT-2001) occupational classification standard. Cox frailty models were used to examine the associations. RESULTS: Of 43,256 in the final sample (excluding those with CVD at baseline and missing data), 25,252 (58.4%) were women, and the mean (± SD, Standard Deviation) age was 50.6 ± 9.5 years. During a median follow-up of 11.9 (IQR, Interquartile Range: 9.5-12.6) years, 3,408 major CVD events (899 myocardial infarctions, 2,400 strokes, 240 incident heart failure, and 764 cardiovascular deaths) were documented. Compared with the reference group (< 4 h per day of sitting), the risk of major CVD events was positively associated with increasing sitting time among manual workers (HR, 1.20; 95% CI, 1.05-1.37 for 6-8 h per day; HR, 1.43; 95% CI, 1.12-1.82 for ≥ 8 h per day), while the risk among non-manual workers was greater for those reporting daily sitting times of more than 8 h (HR, 1.86; 95% CI, 1.18-2.95). Similar trends were observed when CVD mortality and incidence were analysed separately. CONCLUSIONS: Longer daily sitting time was associated with an increased risk of major CVD in both manual and non-manual occupational groups, and the risk was especially high among non-manual workers. Our findings highlight the importance of including measures to reduce sedentary behaviour within a comprehensive strategy to reduce the burden of cardiovascular disease in China.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".