Association of Added Sugars Intake with Micronutrient Adequacy in US Children and Adolescents: NHANES 2009–2014
Bibliographic record
Abstract
BACKGROUND: A concern about the excessive consumption of added sugars is the potential for micronutrient dilution, particularly in children and adolescents; however, the evidence is inconsistent. OBJECTIVE: We examined the associations between added sugars intake and micronutrient adequacy in US children and adolescents using data from NHANES 2009-2014. METHODS: = 4331) were assigned to deciles of added sugars intake based on the average of 2 d of dietary recall. Usual intake of micronutrients was determined using 2 dietary recalls and the National Cancer Institute method. Within each age group, regression analyses were used to assess the relationship between added sugars intake decile and percentage of the population below the estimated average requirements (EARs) for 17 micronutrients. RESULTS: < 0.01) between added sugars intake and percentage of the population (aged 2-18 y) below the EAR were found only for calcium, magnesium, and vitamin D. These associations virtually disappeared after dropping the 2 highest and lowest deciles of intake, suggesting a threshold effect; intakes below approximately 19% of calories from added sugars were generally not associated with micronutrient inadequacy. CONCLUSIONS: As added sugars intake increased, there was a threshold above which an increase in the prevalence of inadequate intakes for calcium, magnesium, and vitamin D among US children and adolescents was observed. However, even at the lower deciles of added sugars, large percentages of the population were below the EAR for these nutrients, suggesting that adequate intakes of these nutrients are difficult to achieve independent of added sugars intake.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".