Validation of a quantitative FFQ for a study of diet and risk of colorectal adenoma among Japanese Brazilians
Bibliographic record
Abstract
OBJECTIVE: To assess the validity of a 161-item quantitative FFQ (QFFQ) that was developed to evaluate dietary risk factors for a colorectal adenoma case–control study. DESIGN: A cross-sectional validation study of the QFFQ against 4 d food diary using Pearson correlation coefficients, cross-classification, weighted k statistics and Bland–Altman plotting. SETTING: Two hospitals in Sa˜o Paulo, Brazil. SUBJECTS: Ninety-seven healthy Japanese-Brazilian adults (40–75 years) were recruited. One participant was excluded from the analysis due to unusual energy intake report. RESULTS: Mean daily nutrient intakes from the QFFQ were higher than from the food diary. The mean Pearson correlation coefficient for nutrient intakes between the QFFQ and the average of the 4 d food diary was 0?43, and increased to 0?45 after correcting correlations for attenuation due to residual day-to-day variation in the food diary measurements. Adjustment for total energy and further adjustment for age and gender decreased the correlation; however, 77% of observations remained in the same or adjacent quartiles with a mean weighted k of 0?22. Bland–Altman plots on loge-transformed data showed no linear trend between the differences and means for energy, fat, protein, total folate and vitamin C. Compared with the food diary, the QFFQ showed consistently reasonable performance for dietary fibre, total folate, retinol, riboflavin and vitamin C. CONCLUSIONS: This investigation supports the relative validity of the QFFQ as a method for assessing long-term dietary intake. The instrument will be a useful tool in the analysis of diet–adenoma associations in the case–control study.
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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 | 0.013 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".