Physical Activity, Obesity, Energy Intake, and the Risk of Non-Hodgkin's Lymphoma: A Population-based Case-Control Study
Bibliographic record
Abstract
The authors conducted a population-based case-control study of 1,030 cases with histologically confirmed, incident non-Hodgkin's lymphoma (NHL) and 3,106 controls to assess the impact of recreational physical activity, obesity, and energy intake on NHL risk in Canada from 1994 to 1997. Compared with those for subjects in the lowest quartiles of total recreational physical activity, multivariable-adjusted odds ratios for subjects in the highest quartile were 0.79 (95% confidence interval (CI): 0.59, 1.05) for men and 0.59 (95% CI: 0.42, 0.81) for women. Obesity (body mass index > or = 30 kg/m2) was associated with odds ratios of 1.59 (95% CI: 1.18, 2.12) for men and 1.36 (95% CI: 1.00, 1.84) for women. For men and women with a lifetime maximum body mass index of > or = 30 kg/m2, respective odds ratios were 1.55 (95% CI: 1.16, 2.06) and 1.10 (95% CI: 0.83, 1.46). For men and women in the highest quartiles of calorie intake, respective odds ratios were 1.95 (95% CI: 1.45, 2.62) and 1.13 (95% CI: 0.84, 1.52). Some differences were found between histologic subtypes of NHL for these associations. This study suggests that recreational physical activity decreases NHL risk, while obesity and excess calorie intake increase it. More studies are needed to confirm these results, especially the differences between histologic subtypes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".