MétaCan
Menu
Back to cohort
Record W3168611962 · doi:10.1093/cdn/nzab053_014

Contribution of Dairy Foods to Energy and Nutrient Intakes in Children and Adults: Analysis of Nhanes 2015–2018

2021· article· en· W3168611962 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Developments in Nutrition · 2021
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsImpact
Fundersnot available
KeywordsRiboflavinNutrientDairy foodsNational Health and Nutrition Examination SurveyFood scienceVitaminDietary Reference IntakeFood groupEnvironmental healthMedicineVitamin B12Total energyAnimal scienceBiologyPopulationPsychology

Abstract

fetched live from OpenAlex

Dairy foods are foundational foods in healthy eating patterns. Consumption of dairy foods helps both children and adults meet the recommendations of a variety of essential nutrients. Accordingly, the objective of this study was to determine the contribution of total dairy, milk, cheese, and yogurt to energy and nutrient intake in children and adults. Twenty-four-hour dietary recall data from children age 2–18 (n = 5038) and adults age 19–99 (n = 9813) participating in the National Health and Nutrition Examination Survey (NHANES) 2015–2016 and 2017–2018 were analyzed. Intakes (both absolute amounts and as a percentage of total intake) of energy and nutrients were determined for all food groups using the USDA food category system. Data were generated on an as consumed basis and on a disaggregated basis; the latter approach reallocated energy and nutrients from milk and cheese found in other foods (e.g., pizza) back to the respective dairy food group. Total dairy was defined as milk, cheese, and yogurt in this analysis. On a disaggregated basis, total dairy provided 14.2% and 9.7% of total kcal/d in children and adults, respectively. At current consumption levels, milk, cheese, and yogurt contributed 61.6% of calcium, 65.8% of vitamin D, 22.8% of potassium, 23.7% of protein, 38.5% of vitamin A, 38.3% of vitamin B12, 31.1% of riboflavin, 36.3% of phosphorus, 22.7% of zinc, and 18.1% of magnesium in children, on average. Dairy foods also contributed 19% of total fat, 31.1% of saturated fat, 13.9% of sodium, and 4.7% of added sugar to the diets of children. Similarly, in adults, milk, cheese, and yogurt contributed 49.5% of calcium, 45.9% of vitamin D, 11.6% of potassium, 15.7% of protein, 26.6% of vitamin A, 24.9% of vitamin B12, 18.6% of riboflavin, 25% of phosphorus, 15.5% of zinc, and 9.4% of magnesium to the diet, on average. Total dairy also provided 14.2% of total fat, 24.8% of saturated fat, and 10.1% of sodium in adults. Milk was the top source of calcium and vitamin D in both children and adults. Milk, cheese, and yogurt remain significant sources of key nutrients for children and adults, including three out of the four underconsumed nutrients of public health concern (vitamin D, calcium, and potassium) as defined by the 2020 Dietary Guidelines for Americans. National Dairy Council.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.283
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it