Development of a Food Frequency Questionnaire: For Toddlers of Low-German-Speaking Mennonites from Mexico
Bibliographic record
Abstract
PURPOSE: Little is known about dietary intakes in toddlers of Low-German-Speaking Mennonites from Mexico, although some of these toddlers might be at risk for nutritional deficiencies. A 97-item, culturally sensitive, interviewer-administered food frequency questionnaire (FFQ) was developed and validated for health professionals to assess dietary intake in these children aged 12 to 36 months. METHODS: Cultural foods on the FFQ were determined via focus groups; a pilot study tested content and formatting. The FFQ was administered to parents/caregivers of 22 toddlers in a southern Ontario community of Low-German-Speaking Mennonites from Mexico. Validity was determined by comparing nutrient intakes from the FFQ and from the 24-hour recalls, using Bland-Altman plots, Pearson correlations, and Student's t-tests. Test-retest reliability was compared between two FFQ administrations (n=14) one month apart, via intraclass correlations (ICCs). RESULTS: Bland-Altman plots showed good agreement between the FFQ and the 24-hour recall; Pearson correlations between methods were significant for protein, folate, calcium, and caffeine. Student's t-tests were not significantly different between methods for 11 of 12 nutrients. Test-retest reliability was good on the basis of acceptable ICC for eight of 12 nutrients. CONCLUSIONS: The prevalence of nutrient inadequacies was low, except for folate. These results are promising for implementation of a simple, quick, culturally sensitive FFQ with the potential to provide reliable estimates of mean intakes in toddlers of Low-German-Speaking Mennonites from Mexico.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".