Cancer incidence attributable to inadequate physical activity in Alberta in 2012
Bibliographic record
Abstract
BACKGROUND: Physical inactivity has been consistently associated with increased risk of colorectal, endometrial, breast (in postmenopausal women), prostate, lung and ovarian cancers. The objective of the current analysis was to estimate the proportion and absolute number of site-specific cancer cases attributable to inadequate physical activity in Alberta in 2012. METHODS: We used population attributable risks to estimate the proportion of each site-specific cancer attributable to inactivity. Relative risk estimates were obtained from the epidemiological literature, and prevalence estimates were calculated with the use of data from the Canadian Community Health Survey cycle 2.1 (2003). Respondents who acquired 1.5-2.9 kcal/kg per day and less than 1.5 kcal/kg per day of physical activity were classified as moderately active and inactive, respectively, and both levels were considered inadequate for mitigating cancer risks. We obtained age-, sex- and site-specific cancer incidence data from the Alberta Cancer Registry for 2012. RESULTS: About 59%-75% of men and 69%-78% of women did not engage in adequate physical activity. Overall, 13.8% of cancers across all associated cancers were estimated to be attributable to inadequate physical activity, representing 7.2% of all cancers diagnosed in Alberta in 2012. Suboptimal levels of physical activity had a greater impact among women: the proportion of all associated cancers attributable to inadequate physical activity was 18.3% for women and 9.9% for men. INTERPRETATION: A substantial proportion of cancer cases diagnosed in Alberta were estimated to be attributable to inadequate physical activity. With the high prevalence of physical inactivity among adults in the province, developing strategies to increase physical activity levels could have a notable impact on reducing future cancer burden in Alberta.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".