Validation of a Phytoestrogen Food Frequency Questionnaire with Urinary Concentrations of Isoflavones and Lignan Metabolites in Premenopausal Women
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to examine the association between dietary intake of phytoestrogens estimated by a food frequency questionnaire (FFQ) with urinary metabolites. METHODS: Participants were 26 premenopausal, Caucasian women aged 25 to 42 years. Dietary intake of isoflavones (genistein and daidzein) and lignans (secoisolariciresinol and matairesinol) were estimated by a 53-item interviewer-administered FFQ on two occasions, reflecting 'habitual' (previous 2 months) and 'recent' (previous 2 days) dietary intake. Isoflavone (genistein, daidzein) and lignan (enterolactone, enterodiol and secoisolariciresinol) concentrations were measured in 24-hour urine samples by gas chromatography-mass spectrometry. Correlations between FFQ (habitual and recent, separately) and urinary metabolite values were assessed using Spearman correlation coefficients. RESULTS: Mean habitual isoflavone and lignan intakes were 13.7 mg/day and 13.8 mg/day, respectively. Mean urinary concentrations of isoflavones and lignans were 17.4 micromol/day and 20.6 micromol/day, respectively. Recent and habitual isoflavone intakes were correlated with urinary excretion of metabolites (r = 0.64, p < 0.001 and r = 0.54, p = 0.004, respectively). Urinary excretion of lignans was also modestly correlated with recent and habitual lignan intakes (r = 0.46, p = 0.02 and r = 0.40, p = 0.05, respectively). CONCLUSIONS: Our results support the use of this FFQ as a measure of dietary isoflavone and lignan intake in epidemiological studies.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".