Household food insecurity among persons with disabilities in Canada: Findings from the 2021 Canadian Income Survey
Notice bibliographique
Résumé
Background: Income-related food insecurity is an important determinant of health. Persons with disabilities are at a higher risk of experiencing household food insecurity (HFI) than those without disabilities. The main objectives of this study were to estimate the prevalence of HFI for persons with different types, numbers, and severity of disabilities, and to examine sociodemographic correlates of HFI among this group. Data and methods: Data from the 2021 Canadian Income Survey (CIS) were used. Disability status was assessed using the short version of the Disability Screening Questions module for one randomly selected household respondent. The Household Food Security Survey Module measured HFI as marginal, moderate, or severe. Weighted descriptive and multivariable analyses were conducted to estimate the prevalence of HFI and analyze the association between various socioeconomic factors and HFI among the study sample. Results: Among CIS participants with disabilities (30% of the total CIS sample: 31 million persons), 26% reported some level of HFI, including 8% with severe HFI. The prevalence of HFI was 13% among those without disabilities. The prevalence of HFI was highest among those with learning, memory, cognition, and seeing disabilities (each at 36%). Levels of HFI were higher for those with more severe disabilities and with a greater number of disabilities. For persons with disabilities, the odds of HFI were two times higher, compared with persons without disabilities (adjusted odds ratio [AOR]: 2.5 [95% confidence interval (CI): 2.2, 2.7]), after adjustment for a range of sociodemographic covariates. Persons with disabilities who were in the lowest income quintile (AOR: 4.0 [95% CI: 3.2, 4.9]) and aged 45 to 54 (AOR: 2.9 [95% CI: 2.1, 4.1]) had the highest odds of HFI, compared with other persons with disabilities living in wealthier households and those aged 65 and older, respectively. Other risk factors included being in a one-parent household, living in the Prairies, and living in a dwelling not owned by the household. Interpretation: HFI prevalence among CIS participants with disabilities was higher than for persons without disabilities, even after adjustment for well-documented sociodemographic risk factors. Consistent monitoring of HFI among persons with disabilities can help inform any ongoing or newly developed poverty reduction strategies for this population.
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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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| 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 ».