Sleep and Cancer Incidence in Alberta's Tomorrow Project Cohort
Bibliographic record
Abstract
Abstract We aimed to investigate the association between self-reported sleep duration and sleep timing midpoint with all- and site-specific cancer incidence in Alberta's Tomorrow Project (ATP) cohort. Methods: The analysis for sleep duration included 46,300 Albertans aged 35–65 years at baseline from the ATP cohort recruited from 2001–2015. Sleep timing midpoint (wake-time – ½ sleep duration) was assessed in a subset of ATP participants (n = 19,820). Cancer incidence was determined through record linkage with the Alberta Cancer Registry in December 2016. Cox proportional hazard regression models evaluated the effects of sleep duration and sleep timing midpoint categories on all- and site-specific (breast, colorectal, lung, prostate, endometrial and hematologic) cancer incidence. Models were adjusted for age, sex (non sex-specific cancers), highest level of education, total household income, marital status, alcohol intake, smoking status, body mass index, family history of cancer, presence of at least one medical condition/co-morbidity, menopausal status (female cancers only) and sleep duration (sleep timing midpoint analysis only). Results: By 2016, there were 3,034 incident cases of cancer in this cohort. A statistical trend was noted for an increased risk of all cancers in participants reporting > 9 hours of sleep/night compared to 7–9 hours of sleep/night (hazard ratio (HR) = 1.16, 95% confidence interval (CI): 0.98–1.36; P = 0.08). Reporting > 9 hours of sleep/night compared to 7–9 hours of sleep/night was also associated with an increased incidence of endometrial cancer (HR = 2.09, 95% CI: 1.16–3.76; P = 0.01). A later sleep timing midpoint (>4:08 AM) versus an intermediate sleep timing midpoint (3:47 AM–4:08 AM) was associated with an increased risk of all (HR = 1.19, 95% CI: 1.03–1.37; P = 0.02) and breast (HR = 1.64, 95% CI: 1.18–2.26; P = 0.003) cancer incidence. Conclusions: These novel findings provide evidence regarding the important role of sleep in cancer etiology. Interventions that put emphasis on proper sleep hygiene for cancer prevention are needed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".