Dairy Foods, Calcium, and Colorectal Cancer: A Pooled Analysis of 10 Cohort Studies
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
BACKGROUND: Studies in animals have suggested that calcium may reduce the risk of colorectal cancer. However, results from epidemiologic studies of intake of calcium or dairy foods and colorectal cancer risk have been inconclusive. METHODS: We pooled the primary data from 10 cohort studies in five countries that assessed usual dietary intake by using a validated food frequency questionnaire at baseline. For most studies, follow-up was extended beyond that in the original publication. The studies included 534 536 individuals, among whom 4992 incident cases of colorectal cancer were diagnosed between 6 and 16 years of follow-up. Pooled multivariable relative risks for categories of milk intake and quintiles of calcium intake and 95% confidence intervals (CIs) were calculated. All statistical tests were two-sided. RESULTS: Milk intake was related to a reduced risk of colorectal cancer. Compared with the lowest category of intake (<70 g/day), relative risks of colorectal cancer for increasing categories (70-174, 175-249, and > or =250 g/day) of milk intake were 0.94 (95% CI = 0.86 to 1.02), 0.88 (95% CI = 0.81 to 0.96), and 0.85 (95% CI = 0.78 to 0.94), respectively (P(trend)<.001). Calcium intake was also inversely related to the risk of colorectal cancer. The relative risk for the highest versus the lowest quintile of intake was 0.86 (95% CI = 0.78 to 0.95; P(trend) =.02) for dietary calcium and 0.78 (95% CI = 0.69 to 0.88; P(trend)<.001) for total calcium (combining dietary and supplemental sources). These results were consistent across studies and sex. The inverse association for milk was limited to cancers of the distal colon (P(trend)<.001) and rectum (P(trend) =.02). CONCLUSION: Higher consumption of milk and calcium is associated with a lower risk of colorectal cancer.
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 | 0.001 |
| 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