Changes in Physical Activity and Risk of Cancer, Findings from the UK Biobank Study
Bibliographic record
Abstract
BACKGROUND: Most studies investigating physical activity and cancer risk used a single-time measure of physical activity. The present analysis investigates whether changes in physical activity during midlife influence cancer risk. METHODS: A prospective cohort of adults ≥40 years from the UK Biobank who provided self-reported physical activity data via the International Physical Activity Questionnaire at both baseline (2007-2010) and follow-up (2012-2013) was analyzed. Changes in physical activity were classified as decreased, maintained, or increased between these two time points. Incident cancers were ascertained up to May 13, 2022. Multivariable Cox regressions were used to examine the associations between changes in physical activity and the risk of cancer overall, by sex, and by obesity- versus nonobesity-related cancers and for breast and prostate cancers. RESULTS: A total of 16,792 participants [mean (SD) age, 56.8 (7.4); 8,421 (50.2%) females] provided repeated data on physical activity. During a median follow-up of 8.3 years, 1,397 incident cancer cases occurred. No statistically significant associations between changes in physical activity and overall cancer risk were found. Increasing physical activity from low to higher levels was associated with a lowered risk of obesity-related cancer [HR = 0.72; 95% confidence interval (CI), 0.54-0.95], particularly for the risk of breast cancer (HR = 0.61; 95% CI, 0.36-1.04). Females who decreased their physical activity from high to lower levels had an elevated cancer risk (HR = 1.47; 95% CI, 1.02-2.11). CONCLUSIONS: Increasing physical activity over time was associated with a lower risk of developing obesity-related cancers, particularly breast cancer. IMPACT: Our findings suggest that behavioral changes to increase physical activity in midlife may help reduce cancer risk.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".