Serum Folate and Cancer Mortality Among U.S. Adults: Findings from the Third National Health and Nutritional Examination Survey Linked Mortality File
Bibliographic record
Abstract
BACKGROUND: The relation between folate status and cancer is controversial. Several epidemiologic studies have suggested that increased folate intake is associated with reduced risk of various cancers, others have found no such associations, and a few have suggested that high folate intake might increase the risk of certain cancers. METHODS: Using data from the Third National Health and Nutrition Examination Survey (NHANES III) Mortality File, a prospective cohort study of a nationally representative sample of 14,611 U.S. adults, we conducted Cox proportional hazards regression modeling to investigate the association of baseline serum folate concentrations and all-cancer mortality determined from linked death certificate data. RESULTS: Relative to the lowest quintile of serum folate (<3.0 ng/mL), the multivariable-adjusted hazard ratios across quintiles 2 to 5 were: 1.61 [95% confidence interval (95% CI), 1.11-2.32], 1.00 (95% CI, 0.65-1.49), 1.39 (95% CI, 0.96-2.03), and 0.85 (95% CI, 0.59-1.22). These findings did not differ substantially by age or sex, but the higher risk for those in the second quintile appeared limited to non-Hispanic whites. CONCLUSION: These findings suggest that there may be a nonlinear relationship between folate status and the risk of all-cancer mortality such that persons with low, but not grossly deficient, serum blood folate concentrations may be at increased risk. Further study is needed to determine whether these findings are due to chance, and if not, to clarify their biological basis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".