Which food literacy dimensions are associated with diet quality among Canadian parents?
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore associations between different food literacy dimensions and diet quality among a sample of Canadian parents and examine differences in the prevalence of food literacy items between mothers and fathers. Design/methodology/approach Parents responsible for food preparation (n=767) completed an online survey including dietary intakes and 22 items across five dimensions of food literacy (knowledge, planning, cooking, food conceptualisation and social aspects). Differences between genders for each item were analysed withχ2tests. The healthy eating index (HEI) adapted to the Canadian Food Guide (CFG) was computed from a food frequency questionnaire. Associations between HEI scores and each item were analysed with linear regression models, controlling for sociodemographic variables and multiple testing. Findings Of parents responsible for food preparation, 81 per cent were mothers. The mean HEI score was 76.6 (SD: 10.6) and mothers reported healthier diets in comparison to fathers (p=0.01). More mothers than fathers used CFG recommendations, selected foods based on nutrition labels, made soups, stews, muffins and cakes from scratch and added fruits and vegetables to recipes (p<0.05). More fathers reduced the salt content of recipes than mothers (p=0.03). Two knowledge items and seven food conceptualisation items were significantly associated with better HEI, after controlling for covariates and multiple testing. Planning items, cooking skills and social aspects were not significantly associated with HEI. Originality/value This study investigates multiple dimensions of food literacy and identifies knowledge and food conceptualisation as potential targets for future interventions involving parents responsible for household meal preparation. This study highlights the importance of considering gender differences in food literacy.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".