Development and Validation of a Food Frequency Questionnaire for Preschool Children Using Multiple Methods
Bibliographic record
Abstract
Background: The ability to determine the relationship between diet and health outcomes in children requires reproducible and validated long-term dietary assessment tools such as food frequency questionnaire (FFQ). Objective: To test the reproducibility and relative validity of a FFQ for young children using 24-hour food recalls (24HRs), anthropometric measurements, and a comprehensive feeding practices questionnaire (CFPQ). Methods: Children (aged 5-6) and their mothers were recruited during one school-year (2008) from preschools. Children's anthropometric measurements were obtained. Mothers provided during a personal interview on three occasions a 110-item semiquantitative FFQ, 24HRs and CFPQ. Pearson-correlation coefficients were calculated between the results of the FFQ and 3*24HR. Validity coefficients between the FFQ and the different measurements were calculated. Scores of the 12 factors of the CFPQ were calculated and related to dietary intake. Results: Sixty-six healthy children (47% boys) were recruited. Pearson's correlations between the average of the FFQs and 3*24HRs ranged from 0.3-0.6 (P<0.05). The highest correlation coefficients were 0.59 for total fat intake and 0.56 for energy. Dietary intake of energy and carbohydrates differed significantly (P=0.05, 0.001 respectively) across the three BMI z-score levels (normal-weight, overweight, obese) and the three waist circumference tertiles (0.019, 0.006 respectively). Obesogenic factors from the CFPQ correlated with consumption of empty calories like sweets, snacks, junk foods and sweet drinks. Conclusions: The modified FFQ is a relatively valid instrument to estimate mean energy intake in preschool children. The questionnaire performs reasonably well to rank children with respect to macronutrients intake as well as obesogenic food groups.
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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 | 0.021 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".