The Economic Burden of Cancers Attributable to Tobacco Smoking, Excess Weight, Alcohol Use, and Physical Inactivity in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The purpose of the present study was to calculate the proportion of cancers in Canada attributable to tobacco smoking (ts), alcohol use (au), excess weight (ew), and physical inactivity (pia); to explore variation in the proportions of those risk factors (rfs) over time by sex and province; to estimate the economic burden of cancer attributable to the 4 rfs; and to calculate the potential reduction in cancers and economic burden if all provinces achieved rf prevalence rates equivalent to the best in Canada. METHODS: We used a previously developed approach based on population-attributable fractions (pafs) to estimate the cancer-related economic burden associated with the four rfs. Sex-specific relative risk and age- and sex-specific prevalence data were used in the modelling. The economic burden was adjusted for potential double counting of cases and costs. RESULTS: In Canada, 27.7% of incident cancer cases [95% confidence interval (ci): 22.6% to 32.9%] in 2013 [47,000 of 170,000 (95% ci: 38,400-55,900)] were attributable to the four rfs: ts, 15.2% (95% ci: 13.7% to 16.9%); ew, 5.1% (95% ci: 3.8% to 6.4%); au, 3.9% (95% ci: 2.4% to 5.3%); and pia, 3.5% (95% ci: 2.7% to 4.3%). The annual economic burden attributable to the 47,000 total cancers was $9.6 billion (95% ci: $7.8 billion to $11.3 billion): consisting of $1.7 billion in direct and $8.0 billion in indirect costs. Applying the lowest rf rates to each province would result in an annual reduction of 6204 cancers (13.2% of the potentially avoidable cancers) and a reduction in economic burden of $1.2 billion. CONCLUSIONS: Despite substantial reductions in the prevalence and intensity of ts, ts remains the dominant risk factor from the perspective of cancer prevention in Canada, although ew and au are becoming increasingly important rfs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it