Validity and Reliability of a Water Frequency Questionnaire to Estimate Daily Total Water Intake in Adults
Bibliographic record
Abstract
The purpose of this investigation was to assess the validity and reliability of a seven-day water frequency questionnaire (TWI-FQ) to estimate daily total water intake (TWI) in comparison to a water turnover objective reference value via deuterium oxide (D2O). Data collection occurred over 3 weeks, with a wash-out period during week two. Healthy adults (n = 98; 52% female; 41 ± 14 y; BMI, 26.4 ± 5.5 kg·m−2) retrospectively self-reported consumption frequencies of 17 liquids and 35 foods with specified volumes/amounts for weeks one and three via TWI-FQ. Standard water content values were utilized to determine the volume of water consumed from each liquid and food for calculation of mean daily TWI for each week. Diet records were completed daily during week two to estimate metabolic water production. To assess validity of the TWI-FQ, participants consumed D2O at the start of each week and provided urine samples immediately before ingestion, the following day, and at the end of the week to calculate water turnover. Metabolic water was subtracted from water turnover to estimate TWI. TWI-FQ validity was assessed via Bland-Altman plot for multiple observations. Reliability was assessed via intraclass correlation and Pearson's correlation between weeks. TWI-FQ significantly underestimated D2O TWI by −350 ± 1,431 mL·d−1 (95% confidence interval (CI): −551, −149 mL·d−1). TWI-FQ TWI was significantly correlated (r = 0.707, P <0.01) and not different (198 ± 1,180 mL·d−1, 95% CI: −38, 435 mL·d−1) between weeks. TWI-FQ intraclass correlation = 0.706 was significant [95% CI: 0.591, 0.793; F(97, 98) = 5.799], indicating moderate test-retest reliability. While this tool would not be suitable for individual TWI assessment, the magnitude of bias may be acceptable for assessment at the sample-level.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".