Validation of a culturally appropriate quantitative food frequency questionnaire for Inuvialuit population in the Northwest Territories, Canada
Bibliographic record
Abstract
BACKGROUND: The estimation of dietary intake in population-based studies is often assessed by a food frequency questionnaire (FFQ). This present study aimed to establish the validity of a 142-item quantitative FFQ (QFFQ) developed to assess dietary intake in a population living in the Northwest Territories, Canada, and undergoing rapid nutrition transition. METHODS: Sixty-four randomly selected Inuvialuit adults were recruited. The mean of one to three 24-h recalls was used as the reference to measure the validity of the QFFQ. Spearman rank correlations (ρ), cross-classification and weighted kappa were computed as measures of concordance, adjusting for the daily dietary intake variations in the recalls. Bland - Altman plots were used for additional assessment. RESULTS: Four participants with daily energy intake of >25.1 MJ were not included in the analysis. For all nutrients, mean daily intake estimations were higher from the QFFQ than from the recalls. De-attenuated ρ's for macronutrients ranged from 0.33 (protein) to 0.45 (carbohydrate). The best de-attenuated ρ amongst micronutrients was observed for vitamin C (0.53). Overall correlation between the two dietary tools improved after correction for within-person variance (from 0.32 to 0.35). When nutrient intakes were categorised into quartiles, the QFFQ and 24-h recalls indicated relative agreement (same or adjacent quartiles) for 77% for energy and macronutrients, 86% for total sugar and 72% for micronutrients. Bland-Altman plots showed a tendency for increased scatter of the differences at higher intakes. CONCLUSIONS: The QFFQ developed is valid and can be used to assess usual dietary intake and dietary adequacy, determine the contribution of foods to specific nutrient intakes, and identify dietary risk factors for chronic disease amongst Inuvialuit.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".