Red blood cell folate levels in Canadian Inuit women of childbearing years: influence of food security, body mass index, smoking, education, and vitamin use
Bibliographic record
Abstract
BACKGROUND: The benefits of folic acid for prevention of congenital anomalies are well known. For the Inuit of Canada, where vitamin use is low and access to folate-rich foods limited, fortification is likely a major source of intake. We sought to determine whether red blood cell folate (RBCF) levels of Inuit women reached accepted target levels. METHODS: The Inuit Health Survey, 2007-2008, included evaluation of RBCF levels among 249 randomly selected non-pregnant women of reproductive age. Using descriptive statistics and linear regression analyses, RBCF levels were assessed and compared across several socio-demographic variables to evaluate the characteristics associated with RBCF status. RESULTS: Mean (SD) RBCF levels of 935.5 nmol/L (± 192) reached proposed target levels (> 906 nmol/L); however, 47% of women had lower than target levels. In bivariate analysis, non-smoking, higher education, higher income, food security, increased body mass index, and vitamin use were each significantly associated with higher RBCF. Increased levels of smoking had a negative association with RBCF levels (- 5.8 nmol/L per cigarette smoked per day (p = 0.001)). A total of 6.8% of women reported taking vitamin supplements, resulting in a 226 nmol/L higher RBCF level on average compared to non-users (p < 0.001). CONCLUSION: While mean levels of folate reached target levels, this was largely driven by the small number of women taking vitamin supplements. Our results suggest that folate status is often too low in Inuit women of childbearing years. Initiatives to improve food security, culturally relevant education on folate-rich traditional foods, vitamin supplements, and smoking cessation/reduction programs may benefit Inuit women and improve birth outcomes.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".