Harmonized Cross-Sectional Surveys Focused on Fluid Intake in Children, Adolescents and Adults: The Liq.In7 Initiative
Bibliographic record
Abstract
OBJECTIVE: To assess the intake of water and all other beverages in children, adolescents and adults. METHODS: Three thousand six hundred eleven children (8 ± 2 years), 8,109 adolescents (13 ± 2 years) and 16,276 adults (40 ± 14 years) (47% men) were recruited in 15 cross-sectional surveys (liquid intake across 7 days, Liq.In7 study) and completed a 7-day fluid-specific record to assess total fluid intake (TFI), where TFI was defined as the sum of drinking water and other type of beverages. RESULTS: The median TFI was 1.2, 1.2 and 1.8 liters/day in children, adolescents and adults respectively, with important differences observed between countries. Only 39% of children, 25% of adolescents and 51% of adults met the European Food Safety Authority adequate intake (AI) recommendations of water from fluids. In the surveys of Spain, France, Belgium, Germany, Turkey, Iran, Indonesia and China, water was the major contributor (47-78%) to TFI. In the adult surveys of UK, Poland, Japan and Argentina, hot beverages were the highest contributor to TFI. The fluid intake of children and adolescents in Mexico, Brazil, Argentina and Uruguay was characterized by a contribution of juices and sweet beverages that was as important as the contribution of water to TFI. CONCLUSION: Given that a relatively high proportion of subjects, especially children and adolescents, failed to meet the recommended AI of water from fluids and that water intake was not the highest contributor to TFI in all countries, undertaking actions to increase water intake are warranted.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".