Food Consumption Patterns: In Preschool Children
Bibliographic record
Abstract
PURPOSE: Healthy eating during early childhood is important for growth and development. Eating Well with Canada's Food Guide (CFG) provides dietary recommendations. We investigated patterns of food consumption among preschool children and attempted to determine whether these children's intakes met nutrition recommendations. METHODS: Between 2005 and 2007, four- and five-year-old children (n=2015) attending 12 Edmonton-region public health units for immunization were recruited for a longitudinal study on determinants of childhood obesity. The children's dietary intake at baseline was assessed using parental reports. RESULTS: Overall, 29.6%, 23.5%, 90.9%, and 94.2% of the children met recommendations for vegetables and fruit, grain products, milk and alternatives, and meat and alternatives, respectively. In addition, 79.5% consumed at least one weekly serving of foods in the "choose least often" group. Significant differences existed in consumption of food groups across socioeconomic and demographic groups. For example, 82.9%, 84.7%, and 75.9% of preschool children from neighbourhoods of low, medium, and high socioeconomic status, respectively, consumed at least one food in the "choose least often" group (χ² =16.2, p<0.001). CONCLUSIONS: Consumption of vegetables and fruit and grain products was low among participants, and intake of "choose least often" foods was high. Consumption of foods also differed among socioeconomic and demographic groups. To encourage healthy eating among children, public health professionals should target groups who do not meet the CFG recommendations.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".