Impact Of 100% Fruit Juice Consumption On Diet And Weight Status Of Children: An Evidence-Based Review
Bibliographic record
Abstract
Consumption of 100% fruit juice remains controversial for its potential adverse impact on weight and displacement of essential foods in the diets of children. A systematic review of the literature published from 1995–2013 was conducted using the PubMed database to evaluate associations between intake of 100% fruit juice and weight/adiposity and nutrient intake/adequacy among children of 1 to 18 years of age. Weight status outcome measures included body mass index (BMI), BMI z-score, ponderal index, obesity, weight gain, adiposity measures, and body composition. Nutrient outcome measures included intake and adequacy of shortfall nutrients. Data extraction and analysis was conducted according to the Academy of Nutrition and Dietetics Evidence Analysis Process. Twenty-two studies on weight status provided evidence that did not support an association between 100% fruit juice consumption and weight/adiposity in children after controlling for energy intake. Limited evidence from eight studies suggests that children consuming 100% fruit juice have higher intake and adequacy of dietary fiber, vitamin C, magnesium, and potassium. Differences in methodology and study designs preclude causal determination of 100% fruit juice as sole influence of weight status or nutrient intake/adequacy of shortfall nutrients. In context of a healthy dietary pattern, evidence suggests that consumption of 100% fruit juice may provide beneficial nutrients without contributing to pediatric obesity.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".