Sedentary Behavior and Prostate Cancer Risk in the NIH–AARP Diet and Health Study
Bibliographic record
Abstract
Sedentary behavior (sitting time) has been proposed as an independent risk factor for some cancers; however, its role in the development of prostate cancer has not been determined. We examined the prospective associations of self-reported daily sitting time and daily television/video viewing time with the risk of developing or dying from prostate cancer among 170,481 men in the NIH-AARP Diet and Health Study. We estimated HRs and 95% confidence intervals (CI) using Cox proportional hazards regression. Between 1996 and 2006, there were 13,751 incident (including 1,365 advanced) prostate cancer cases identified; prostate cancer mortality (through 2008) was 669. No strong or significant association with prostate cancer risk was seen in fully adjusted models for either daily sitting or television/video time. There were some suggestions of effect modification by body mass index (BMI; interaction for television/video time and BMI, P = 0.02). For total prostate cancer risk, television/video time was associated with a slightly elevated, but nonsignificant, increase amongst obese men (HR = 1.28; 95% CI, 0.98-1.69); a null association was observed amongst overweight men (HR = 1.04; 0.89-1.22); and, for men with a normal BMI, television/video time was associated with a nonsignificant risk decrease (HR = 0.82; 95% CI, 0.66-1.01). Similar patterns were observed for total daily sitting and television/video time in advanced prostate cancer and prostate cancer mortality. Sedentary behavior seems to play a limited role in the development of prostate cancer; however, we cannot rule out potential effect modification by BMI or the impact of measurement error on results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".