Prevalence and sociodemographic correlates of food insecurity among post-secondary students and non-students of similar age in Canada
Bibliographic record
Abstract
BACKGROUND: The results of several recent campus-based studies indicate that over half of post-secondary students in Canada are food insecure, but the vulnerability of this group has not been considered in research on predictors of food insecurity in the Canadian population. Our objectives were to (1) compare the prevalence of food insecurity among post-secondary students and non-students of similar age; (2) examine the relationship between student status and food insecurity among young adults while accounting for sociodemographic characteristics; and (3) identify the sociodemographic characteristics associated with food insecurity among post-secondary students. METHODS: Using data from the 2018 Canadian Income Survey, we identified 11,679 young adults aged 19-30 and classified them into full-time postsecondary students, part-time post-secondary students, and non-students. Food insecurity over the past 12 months was assessed with the 10-item Adult Scale from the Household Food Security Survey Module. Multivariable logistic regression analyses were used to estimate the odds of food insecurity by student status while accounting for sociodemographic characteristics, and to identify sociodemographic characteristics predictive of food insecurity among post-secondary students. RESULTS: The prevalence of food insecurity was 15.0% among full-time postsecondary students, 16.2% among part-time students, and 19.2% among non-students. After adjusting for sociodemographic factors, full-time postsecondary students had 39% lower odds of being food insecure as compared to non-students (aOR 0.61, 95% CI 0.50-0.76). Among postsecondary students, those with children (aOR 1.93, 95%CI 1.10-3.40), those living in rented accommodation (aOR 1.60, 95%CI 1.08-2.37), and those in families reliant on social assistance (aOR 4.32, 95%CI 1.60-11.69) had higher adjusted odds of food insecurity, but having at least a Bachelor's degree appeared protective (aOR: 0.63, 95% CI 0.41-0.95). Every $5000 increase in adjusted after-tax family income was also associated with lower adjusted odds of food insecurity (aOR 0.88, 95%CI 0.84-0.92) among post-secondary students. CONCLUSIONS: In this large, population-representative sample, we found that young adults who did not attend post-secondary school were more vulnerable to food insecurity, particularly severe food insecurity, than full-time post-secondary students in Canada. Our results highlight the need for research to identify effective policy interventions to reduce food insecurity among young, working-age adults in general.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".