Prolonged Sitting, Its Combination With Physical Inactivity and Incidence of Lung Cancer: Prospective Data From the HUNT Study
Bibliographic record
Abstract
Background: Prolonged sitting as a major sedentary behavior potentially contributes to illness, but its relation with lung cancer risk is unclear. Prolonged sitting can be presented in physically active or inactive individuals. Those who are extendedly seated and also physically inactive may represent the most sedentary people. We therefore aimed to prospectively examine if total sitting time daily itself or in combination with physical activity is associated with lung cancer incidence overall and histologic types. Methods: We included 45,810 cancer-free adults who participated in the second survey of HUNT Study in Norway (1995-97), with a median follow-up of 18.3 years. Total sitting time daily and physical activity were self-reported at baseline. Lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression was used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Results: In total, 549 participants developed lung cancer during the follow-up. Total sitting time daily was not associated with the incidence of lung cancer overall and histologic subtypes. Compared with participants sitting <8 hours daily and being physically active, those sitting ≥8 hours daily (prolonged sitting) and being physically inactive had an increased incidence of lung cancer (overall: adjusted HR = 1.44, 95% CI: 1.07-1.94; small cell lung cancer: adjusted HR = 2.58, 95% CI: 1.23-5.41). Prolonged sitting only or physical inactivity only was not associated with the incidence of lung cancer. Conclusions: Our study suggested that prolonged sitting was not independently associated with lung cancer incidence. The combination of prolonged sitting and physical inactivity might increase the risk of lung cancer. However, residual confounding by smoking cannot be excluded completely even though smoking was adjusted for with detailed information.
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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 | 0.000 | 0.000 |
| 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".