Cancer incidence attributable to insufficient fruit and vegetable consumption in Alberta in 2012
Bibliographic record
Abstract
BACKGROUND: Sufficient fruit and vegetable consumption (≥ 5 servings/d) has been associated with a probable decreased risk for cancers of the oral cavity, pharynx, larynx, esophagus, stomach and lung (fruit only). The purpose of this study was to estimate the proportion and absolute number of cancer cases in Alberta in 2012 that were attributable to insufficient fruit and vegetable consumption. METHODS: The numbers and proportions of cancers attributable to insufficient fruit and vegetable consumption were estimated using the population attributable risk. Relative risks were obtained from international collaborative panels and peer-reviewed literature. Prevalence data for insufficient fruit and vegetable consumption in Alberta were obtained from the Canadian Community Health Survey (2003, 2004, 2005, 2007/08). Age-, site- and sex-specific cancer incidence data for 2012 were obtained from the Alberta Cancer Registry. RESULTS: The proportion of men consuming 5 or more servings of fruits and vegetables per day ranged from 25.9%-30.4% across age groups; the range among women was 46.8%-51.5% across age groups. The proportion of cancers attributable to insufficient fruit and vegetable consumption in Alberta was highest for esophageal cancer (40.0%) and lowest for lung cancer (3.3%). Overall, 290 cancer cases (1.8%) in Alberta in 2012 were attributable to insufficient fruit and vegetable consumption. INTERPRETATION: Almost 2% of cancers in Alberta can be attributed to insufficient fruit and vegetable consumption. A diet rich in fruits and vegetables has benefits for the prevention of cancer and other chronic diseases; thus, increasing the proportion of Albertans who meet cancer prevention guidelines for fruit and vegetable consumption is a priority.
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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".