Black-white Racial Disparities in Household Food Insecurity from 2005-2014, Canada
Notice bibliographique
Résumé
Abstract Background: Household food insecurity is a public health concern in many high-income countries. Despite two decades of research charting the socio-demographic and geographic correlates of food insecurity in Canada, the relationship between race and vulnerability to food insecurity has not been interrogated. Our objectives were to examine the association of Black-White racial identity and prevalence and severity of household food insecurity in Canada, and understand how racialized vulnerability manifests differently for key sociodemographic predictors. Methods: Data for households with Black and White respondents with complete data on household food insecurity were drawn from the Canadian Community Health Survey cycles from 2005-2014 (N=491,400). Household food insecurity status was assessed using the Household Food Security Survey Module. Bivariate and multivariate logistic and multinomial regression models were run, including respondent’s race and immigration status, as well as six well-established household-level predictors of food insecurity in the general population: household composition, income, housing tenure, highest level of education in the household, main household income source, and province/territory. To test whether the relationship between food insecurity and these predictors differed by race, additional multivariable logistic regression models were run, with race interacted with each predictor individually and predicted probabilities estimated.Results: The weighted prevalence of household food insecurity was 10.0% for white respondents and 28.4% for Black respondents. The odds of Black households being food-insecure compared to white households fell from 3.56 (95% CI: 3.30-3.85), to 1.88 (95% CI: 1.70-2.08) with adjustment for household sociodemographic characteristics. In contrast to white households, there was relative homogeneity of risk of food insecurity among Black sub-groups defined by immigration status, household composition, education, and province of residence. Homeownership was associated with lower probabilities of food insecurity for Black and white households, but the probability among Black owners was similar to that for white renters (14.7% vs. 14.3%). Black households had significantly higher predicted probabilities of food insecurity than their white counterparts across all main sources of household income except child benefits and social assistance.Conclusions: Being racialized as Black appears to be an overriding factor predicting vulnerability to food insecurity for the Black population in Canada.
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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 | 0,004 | 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) | 0,004 | 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 ».