Food insecurity, food skills, health literacy and food preparation activities among young Canadian adults: a cross-sectional analysis
Bibliographic record
Abstract
OBJECTIVE: To assess associations between household food security status and indicators of food skills, health literacy and home meal preparation, among young Canadian adults. DESIGN: Cross-sectional data were analysed using logistic regression and general linear models to assess associations between food security status and food skills, health literacy and the proportion of meals prepared at home, by gender. SETTING: Participants recruited from five Canadian cities (Vancouver (BC), Edmonton (AB), Toronto (ON), Montreal (QB) and Halifax (NS)) completed an online survey. PARTICIPANTS: 1389 men and 1340 women aged 16-30 years. RESULTS: Self-reported food skills were not associated with food security status (P > 0·05) among men or women. Compared to those with high health literacy (based on interpretation of a nutrition label), higher odds of food insecurity were observed among men (adjusted OR (AOR): 2·58, 95 % CI 1·74, 3·82 and 1·56, 95 % CI 1·07, 2·28) and women (AOR: 2·34, 95 % CI 1·48, 3·70 and 1·92, 95 % CI 1·34, 2·74) with lower health literacy. Women in food-insecure households reported preparing a lower proportion of breakfasts (β = -0·051, 95 % CI -0·085, -0·017), lunches (β = -0·062, 95 % CI -0·098, -0·026) and total meals at home (β = -0·041, 95 % CI -0·065, -0·016). Men and women identifying as Black or Indigenous, reporting financial difficulty and with lower levels of education had heightened odds of experiencing food insecurity. CONCLUSIONS: Findings are consistent with other studies underscoring the financial precarity, rather than lack of food skills, associated with food insecurity. This precarity may reduce opportunities to apply health literacy and undertake meal preparation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".