The Food and Nutrition Security for Manitoba Youth (FANS) study: rationale, methods, dietary intakes and body mass index
Bibliographic record
Abstract
BACKGROUND: Good nutrition and access to healthy foods are essential for child growth and development. However, there are concerns that Canadian children do not have a healthy diet, which may be related to dietary choices as well as lack of access to healthy foods. The FANS (Food and Nutrition Security for Children and Youth) study examined the nutrition and food security status of youth in the province of Manitoba, Canada. This paper describes methods, dietary intakes, and body mass index for the FANS study. METHODS: This cross-sectional study included 1587 Manitoba grade nine students who completed a self-administered web-based survey. Data was collected on demographic characteristics, dietary intake (24-h recall), food behaviors, food security, and self-report health indicators. Dietary data was compared to national dietary guidelines (Dietary Reference Intakes and Canada's Food Guide). Mean and median nutrient and food group intakes were calculated with corresponding measures of variability. Chi-square tests compared percentage of respondents not meeting key nutrients and food groups. Significant differences in percentage of total servings for each food group were determined by a Kruskal-Wallis test, and differences between different caloric groups were assessed using Dunn's test for post-hoc comparisons. RESULTS: Half of study respondents were female (50.5%). Median energy intake was higher in males (2281 kcal) compared with females (1662 kcal), with macronutrient distribution of 52%, 16%, and 32% for carbohydrates, protein, and fats respectively. Most participants consumed inadequate fibre (94%), vitamin D (90%), and calcium (73%), while median sodium intakes exceeded recommendations for males but not females. A majority of participants did not meet Health Canada's recommendations for food group servings: Vegetables and Fruit (93%), Milk and Alternatives (74%), Meat and Alternatives (57%) and Grain Products (43%). Other Foods, including sugar sweetened beverages and juice, were consumed by most participants. Higher energy consumers had a greater proportion of food servings coming from Other Foods. 72.1% of students were classified as having a healthy weight and 25% were classified as overweight or obese. CONCLUSION: Poor dietary intakes and body mass index values indicate an urgent need for policy and program strategies to support healthy eating habits and food awareness in Manitoba youth.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".