O1-5.5 Determinants of high folate concentration in the Canadian population
Bibliographic record
Abstract
Introduction Canadians' red blood cell (RBC) folate has shifted towards high concentrations (>1360 nmol/l based on the 97th percentile of Americans post-fortification (NHANES)). Determinants of these high concentrations are poorly understood, though an association has been posited between high intakes of folic acid and adverse health outcomes. This research investigated determinants of high folate concentrations in Canadians. Methods RBC folate concentrations from the nationally representative Canadian Health Measures Survey were examined in participants aged 6–79 years (N=5248). The population was described using frequencies and percentages. Sociodemographic, behavioural and clinical determinants of high RBC folate concentrations were examined using univariate and separate multiple logistic regression models controlling for age and household income. Results The greatest proportion of high concentrations occurred in females (42.5%), higher age groups (6–11 years (36.4%), 12–19 years (25.6%), 20–39 years (32.9%), 40–59 years (44.5%), 60–79 years (53.6%)) and higher income quartiles (33.5% (Q1), 37.6% (Q2), 41.6% (Q3), 46.6% (Q4)). Folic acid containing supplement users had a greater prevalence of high concentrations (62.8%) than non-users (37.2%). Prevalence of high concentrations climbed with increasing intake of fruit/vegetables (>3 times per day (46.8%)) and grain products (>3 times per day (45.5%)). Never smokers (39.5%) and former smokers (49.1%) had a greater prevalence of high concentrations than daily smokers (28.4%). Detailed regression results will be presented at the conference. Conclusion Determinants of high folate concentrations should be considered when refining folic acid supplementation and fortification policies. Future research on the relationship between high folate concentrations and health outcomes is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".