Trends in Orange Juice Consumption and Nutrient Adequacy in Children 2003-2016
Bibliographic record
Abstract
This study aimed to examine secular trends in 100% orange juice (OJ) consumption and trends in nutrient adequacy in children 2-18 years participating in the 2003-2016 National Health and Nutrition Examination Survey. The National Cancer Institute method was used to estimate the usual intake. Ten deciles of OJ consumption were determined based on intakes with non-consumers in the first decile. Nutrient adequacy was determined using the percentage below the Estimated Average Requirement (EAR) or the Adequate Intake (AI) percentage. Linear regression coefficients for changes in intake over time and across deciles of OJ were generated. Approximately 14% of the total sample consumed OJ with a mean intake of 40.0 g/d (77 KJ [0.9% of total energy intake]). Amounts of all 100% fruit juices consumed decreased by 44%, and whole fruit intake increased by approximately 32% from 2003-2016. Consumption of total energy, total carbohydrates, added sugars, and saturated fatty acids decreased. Intakes of folate, riboflavin, zinc, and vitamin C decreased from 2003-2016. The percentage of children below the EAR increased for vitamin C and zinc and decreased for vitamin A from 2003-2016. Percent of children above the AI increased for fiber. Across the deciles of OJ consumption, the percent of children with an inadequate vitamin D intake, calcium, iron, and phosphorus decreased. OJ and other 100% juices were major food sources of many nutrients consumed at levels below recommendations. One strategy to reduce inadequate intake of calcium, phosphorus, and potassium intake is to maintain or increase the consumption of OJ and other 100% juices
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".