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Record W2950957389 · doi:10.1093/cdn/nzz036.p13-006-19

Validation and Reliability of a Water Frequency Questionnaire to Estimate Daily Water Intake in Adults (P13-006-19)

2019· article· en· W2950957389 on OpenAlexaff
Abigail T. Colburn, Evan C. Johnson, François Pérronet, Lisa T. Jansen, Catalina Capitán-Jiménez, J.D. Adams, Isabelle Guelinckx, Erica T. Perrier, Andy Mauromoustakos, Stavros A. Kavouras

Bibliographic record

VenueCurrent Developments in Nutrition · 2019
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsReliability (semiconductor)Water intakeEnvironmental sciencePsychologyReliability engineeringStatisticsEnvironmental healthMedicineMathematicsWater resource managementEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Investigators sought to: 1) evaluate the validity of a water frequency questionnaire (WFQ) to estimate mean daily water intake (WI) in adults through comparison to the gold standard, deuterium oxide (D2O) disappearance, and 2) evaluate reliability of WFQ to estimate WI. Data collection occurred over three weeks, with validity of WFQ (vs. D2O) assessed during week one (W1) and reliability assessed between W1 and week three (W3). Healthy, free-living adults (n = 103; 51% female; 41 ± 14 y; BMI, 26.5 ± 5.5 kg·m–2) consumed D2O (0.1 g·kg–1 lean mass) at the start of W1 and provided urine samples immediately before ingestion, the following day, and at the end of the week to calculate total body water turnover (WTO). Seven day beverage consumption during W1 and W3 was retrospectively estimated using the WFQ. The WFQ included 17 beverage types with specified volumes (e.g., water (8 oz); soft drink (12 oz)) and nine frequency options ranging from ‘Never or less than 1 per week’ to ‘7+ per day’. Investigators converted beverage volumes to mL and calculated WI for each week. Food frequency questionnaires were also completed at the end of both weeks. Diets were analyzed with Nutritional Data System for Research software to estimate water intake from solid foods and metabolic water production by macronutrient oxidation. Water from food and macronutrient oxidation were subtracted from WTO to estimate WI via D2O. WFQ reliability was assessed via intraclass correlation (ICC) and Cronbach α, and validity was assessed via Bland-Altman plots. The mean difference in WI between D2O (2902 ± 1321 mL·day–1) and WFQ (2589 ± 1560 mL·day–1) was –308 ± 166 mL (P = 0.065). No systematic bias was observed between methods (R2 = 0.032, P = 0.071) as 3% of WI variance was explained by differences between methods. WFQ WI was not different between W1 (2589 ± 1560 mL·day–1) and W3 (2441 ± 1334 mL·day–1, P = 0.135). Cronbach α = 0.8415 demonstrated high internal consistency in WI estimation. The ICC was 0.834 (95% CI: 0.754, 0.887), demonstrating good test-retest reliability of WFQ. In conclusion, the WFQ produced reliable WI estimates that were comparable to the gold standard of D2O assessment. This questionnaire may be a practical and easy method for assessing water intake in adults. The study was funded by Danone Research.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.314

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.320
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2019
Admission routes1
Has abstractyes

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