Validity and reliability of a food frequency questionnaire to estimate dietary intake among Lebanese children
Bibliographic record
Abstract
BACKGROUND: Nutritional status during childhood is critical given its effect on growth and development as well as its association with disease risk later in life. The Middle East and North Africa (MENA) region is experiencing alarming rates of childhood malnutrition, both over- and under-nutrition. Hence, there is a need for valid tools to assess dietary intake for children in this region. To date, there are no validated dietary assessment tools for children in any country of the MENA region. The main objective of this study was to examine the validity and reliability of a Food Frequency Questionnaire (FFQ) for the assessment of dietary intake among Lebanese children. METHODS: Children, aged 5 to 10 years (n = 111), were recruited from public and private schools of Beirut, Lebanon. Mothers (proxies to report their children's dietary intake) completed two FFQs, four weeks apart. Four 24-hour recalls (24-HRs) were collected weekly during the duration of the study. Spearman correlations and Bland-Altman plots were used to assess validity. Linear regression models were used to derive calibration factors for boys and girls. Reproducibility statistics included Intraclass Correlation Coefficient (ICC) and percent agreement. RESULTS: Correlation coefficients between dietary intake estimates derived from FFQ and 24-HRs were significant at p < 0.001 with the highest correlation observed for energy (0.54) and the lowest for monounsaturated fatty acids (0.26). The majority of data points in the Bland-Altman plots lied between the limits of agreement, closer to the middle horizontal line. After applying the calibration factors for boys and girls, the mean energy and nutrient intakes estimated by the FFQ were similar to those obtained by the mean 24-HRs. As for reproducibility, ICC ranged between 0.31 for trans-fatty acids and 0.73 for calcium intakes. Over 80 % of study participants were classified in the same or adjacent quartile of energy and nutrients intake. CONCLUSIONS: Findings of this study showed that the developed FFQ is reliable and is also valid, when used with calibration factors. This FFQ is a useful tool in dietary assessment and evaluation of diet-disease relationship in this age group.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".