MétaCan
Menu
Back to cohort
Record W2071878547 · doi:10.1017/s1368980012000699

Nutritional quality of children's school lunches: differences according to food source

2012· article· en· W2071878547 on OpenAlexafffundabout
Jennifer Taylor, Kimberley Hernandez, Jane Mary Caiger, Donna Giberson, Debbie MacLellan, Marva Sweeney‐Nixon, Paul J. Veugelers

Bibliographic record

VenuePublic Health Nutrition · 2012
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsUniversity of AlbertaHealth PEIUniversity of Prince Edward Island
FundersCanadian Institutes of Health Research
KeywordsMicronutrientRiboflavinNiacinVitaminEnvironmental healthFood scienceMedicineAdded sugarNutrientNutrient densityVitamin B12SugarBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the nutritional quality of lunchtime food consumption among elementary-school children on Prince Edward Island according to the source of food consumed (home v. school). DESIGN: Students completed a lunchtime food record during an in-class survey. Dietary adequacy was assessed by comparing median micronutrient intakes with one-third of the Estimated Average Requirement; median macronutrient intakes were compared with the Acceptable Macronutrient Distribution Ranges. The Wilcoxon signed rank test was used to assess differences in nutrient intakes according to source of food consumed. SETTING: Elementary schools in Prince Edward Island, Canada. SUBJECTS: Grade 5 and 6 students (n 1980). RESULTS: Foods purchased at school were higher in nutrient density for ten micronutrients (Ca, Mg, K, Zn, vitamin A, vitamin D, riboflavin, niacin, vitamin B6 and vitamin B12) compared with packed lunch foods from home, which were higher in three micronutrients (Fe, vitamin C and folate). School lunches provided sufficient protein but were higher in sugar and fat than home lunches. Foods brought from home were higher in carbohydrates, fibre and Na than foods purchased at school. CONCLUSIONS: The overall nutritional quality of lunches was poor, regardless of source. A significant proportion of foods consumed by the students came from home sources; these were lower nutritional quality and were higher in Na than foods offered at school. Findings suggest that improving the dietary habits of school-aged children will require a collaborative effort from multiple stakeholders, including parents.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.001
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 score0.026
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.086
GPT teacher head0.347
Teacher spread0.261 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations38
Published2012
Admission routes3
Has abstractyes

Explore more

Same venuePublic Health NutritionSame topicObesity, Physical Activity, DietFrench-language works237,207