Examining the relationship between food security and perceived health among Memorial University students
Bibliographic record
Abstract
Abstract Objectives: The prevalence of student food insecurity at Memorial University of Newfoundland (MUN) is relatively high (58.0%) compared to the national population (12.7%). We explored the relationship between food security status, perceived health, and student experience among MUN students. Methods: Through an online survey of returning MUN students at the St. John’s campus, we assessed food security using Statistics Canada’s Canadian Household Food Security Survey Module (HFSSM), and self-reported physical health, mental health, and stress. We used logistic regression to compare health and stress ratings between students of different food security levels. We thematically coded open-ended responses to describe students’ experiences related to food insecurity. Results: Among the 967 study eligible students, 39.9% were considered food insecure, 28.2% were moderately food insecure, and 11.7% were severely food insecure. After controlling for significant predictors, students who were moderately or severely food insecure were 1.72 [95% CI:(1.20,2.48)] and 2.81 [95% CI:(1.79,4.42)] times as likely to rate their physical health as ‘fair’ or ‘poor’ than food secure students, and 1.66 [95% CI:( 1.22,2.27)] and 4.23 [95% CI: (2.71-6.60] times as likely to rate their mental health as ‘fair’ or ‘poor’ than food secure students, respectively. Conclusion: Food security level experienced by MUN students was closely related to their perceived physical and mental health. As food security level worsened among participants, their self-reported physical and mental health also worsened. Health professionals working with university student populations should screen for food security and consider its relationship to students’ health.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".