A study of fluid intake from beverages in a sample of healthy French children, adolescents and adults
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: To assess the intake of fluid in healthy French children, adolescents, adults and seniors, considering amounts, types of beverages, time and place of consumption. SUBJECTS/METHODS: Data regarding fluid intake were extracted and analyzed from the National Intake Survey, which was conducted in quota samples of the French population (Comportement et Consommations Alimentaires en France study). Seven-day questionnaires were administered to free-living individuals in 2002-2003. A total of 566 children (aged 6-11 years), 333 adolescents (aged 12-19 years), 831 adults (aged 20-54 years) and 443 seniors (aged >or=55 years) were included in this study. RESULTS: The average total intake of fluid was 1-1.3 l per day depending on age groups. Water accounted for about one-half of daily fluid intake. The contribution of other types of beverages varied with age (for example, dairy drinks in children and adolescents; alcoholic drinks in adults and seniors). Intake of sodas (including regular and light) was highest in adolescents (169 ml a day). Beverages were mainly consumed at home during meals. CONCLUSIONS: This is the first description of fluid intake in French children, adolescents, adults and seniors, considering amounts, types of beverages, time and place of intake. It shows that water is the main source of fluid in all age groups. Selection of various types of beverages is different according to age.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".