Prevalence and sociodemographic correlates of food insecurity among post-secondary students and non-students of similar age in Canada
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».