Micronutrient Dilution and Added Sugars Intake in U.S. Adults: Examining This Association Using NHANES 2009–2014
Bibliographic record
Abstract
There is inconsistent evidence regarding the impact of added sugars consumption on micronutrient dilution of the diet. We examined the associations between added sugars intake deciles and nutrient adequacy for 17 micronutrients in U.S. adults 19+ (n = 13,949), 19–50 (n = 7424), and 51+ y (n = 6525) using two days of 24 hour dietary recall data from the National Health and Nutrition Examination Survey (NHANES) 2009–2014 and regression analysis. Added sugars intake deciles ranged from <3.8 to >23.3% of calories among adults 19+ y, with a median intake of 11.0% of calories. Significant associations (p ≤ 0.01) between added sugars intake deciles and percentage of the population below the Estimated Average Requirement (EAR) were found for magnesium, vitamin C, vitamin D, and vitamin E; only the association with magnesium remained significant after dropping the two highest and lowest deciles of intake, suggesting a threshold effect. Intakes below approximately 18% of calories from added sugars were generally not associated with micronutrient inadequacy. However, even at the lower deciles of added sugars, large percentages of the population were below the EAR for these four micronutrients, suggesting that adequate intakes are difficult to achieve regardless 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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".