Adequacy of the intake of vitamins and mineral in women participants in the Mexican National Nutrition Survey 2006 (ENSANUT‐2006)
Bibliographic record
Abstract
Objective To evaluate the adequacy of intake of micronutrients and fiber in women from the ENSANUT‐2006. Methods Dietary intake and compliance with dietary recommendations were estimates for a sample of Mexican women aged >;19 years from ENSANUT‐2006. Food intake came from a food frequency questionnaire. Dietary adequacy was classified into adequate (adequacy >;100%), moderately inadequate (50–99%), and highly inadequate (<50%). Analysis Means of adequacy were estimated through linear and polynomial multiple regression. Results The adequacy for vitamin A varied by age from 69–79%, the following intakes decreased progressively with age: Vitamin C 69–50%, folate 26–12.4%, vitamin B12 56.4–34.4%. For minerals iron decreased from 21.2–12‐13% and increased to 45% in >;50 years of age. Calcium increased with age from 24.9–32.9% and declined to 15.0%. Magnesium intake decreased from 56.6–36.9% and phosphate increased from 57.8–88.2%. The adequacy for fiber increased with age from 12–36%. Discussion We documented evidence about the low dietary intake of vitamins and minerals prevailing in Mexican women, although the coincidence with the prevalence of micronutrients deficiencies only occurred with vitamins A and C, calcium, magnesium.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".