A DASH dietary pattern and the risk of colorectal cancer in Canadian adults
Bibliographic record
Abstract
INTRODUCTION: Colorectal cancer (CRC) is a high incidence cancer affecting many Canadian adults each year. Diet is important in the etiology of CRC with many dietary components identified as potential risk factors. The Dietary Approaches to Stop Hypertension (DASH) diet is a well-established pattern to characterize overall eating. The purpose of this study was to characterize a DASH pattern within the Canadian context and to assess its relationship to the risk of CRC in Canadian adults. METHODS: Unconditional multiple logistic regression with control for confounding variables was performed using data from the National Enhanced Cancer Surveillance Study. Dietary intake was captured for this case-control study through a food frequency questionnaire (FFQ) and categorized into a DASH score ranging from 0 to 10 representing a poor to a strong DASH pattern respectively. RESULTS: Consuming a strong DASH pattern of eating (score ≥ 8) was not common in the 3161 cases and 3097 controls. Overall, only 10.8% of men and 13.6% of women had a strong DASH pattern. Multivariate analysis demonstrated a trend for decreasing risk of CRC in men with increasing DASH scores (p value for trend = .007). Men with a strong DASH score had a 33% reduction in risk of CRC compared to those with a low DASH score. There were no significant trends for women for CRC or for colon or rectal cancers separately. CONCLUSION: Our findings are similar to other researchers suggesting a benefit with a strong DASH pattern associated with a decreased risk of CRC, especially in men. Research should further investigate our gender-based differences.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".