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Enregistrement W7057222401

Household Food Insecurity in Canada Before and During the COVID-19 Pandemic: Findings from the International Food Policy Study 2018-2020

2022· dissertation· en· W7057222401 sur OpenAlexaboutno aff

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2022
Typedissertation
Langueen
DomainePhysics and Astronomy
ThématiqueMagnetic confinement fusion research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFood insecurityPsychological interventionFood securityPandemicPopulationFood processing
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: Food insecurity refers to constrained food access due to inadequate \nfinancial resources. Those living in food-insecure households are at risk for compromised \nnutrition, including inadequate nutrient intakes. Furthermore, food insecurity is linked to \nnumerous diet-related non-communicable diseases, including poor mental health, diabetes, and cardiovascular diseases. Reducing food insecurity is thus an important population health goal to improve nutritional status and reduce non-communicable disease risk. There are numerous sociodemographic factors, such as income, racial identity, and region, that are associated with food insecurity in Canada. Food bank use is considered an indicator of food insecurity, especially in short-term situations, yet the suitability of food bank use as a measure for food insecurity is questionable. The COVID-19 pandemic may have impacted the prevalence of food insecurity in Canada due to reduced income. Examining the relationship between household food insecurity and sociodemographic factors, including how the COVID-19 pandemic may have differential impacts on certain sociodemographic groups, could shed unique insights into effective interventions to ameliorate food insecurity. \n \nResearch Questions: The study addressed four primary research questions: (1) What proportion of adults in the IFPS lived in food-insecure households in 2018, 2019, and 2020, and how has the prevalence of household food insecurity changed over time? (2) Are there significant differences in the proportion of respondents who live in food-insecure households among certain sociodemographic groups before and during the COVID-19 pandemic? (3) What proportion of respondents who live in food-insecure households also report preparing or consuming food collected from a food bank in the past week, and how does the sociodemographic profile of those who did prepare or consume food from a food bank differ from those who didn't? and (4) What proportion of adults self-reported that the COVID-19 pandemic impacted whether their household had enough food to eat? \nMethods: Repeat cross-sectional data were drawn from the International Food Policy Study. Data were collected via self-completed web-based surveys conducted in November-December 2018, 2019, and 2020. Respondents included adults aged 18 to 100 years residing in Canada at the time of the survey. Respondents were recruited using nonprobability-based sampling from the Nielsen Global Panel. Food insecurity was assessed using the Household Food Security Survey Module. Respondents were also asked if they prepared or consumed food that was collected from a food bank in the past week and if COVID-19 had an impact on whether their household had enough food to eat and on their ability to meet their financial obligations in 2020. In model 1, a multinomial regression tested the associations between sociodemographic characteristics and household food insecurity (0=Food secure, 1=Moderate food insecurity, 2=Severe food insecurity), and 2-way interactions with survey year were assessed to examine patterns over time. In model 2, a binary logistic regression examined the associations between sociodemographic characteristics and preparing or consuming food collected from a food bank within the past seven days (0=No, 1=Yes), and 2-way interactions between sociodemographic characteristics and survey year and household food security status were analyzed. In model 3, a multinomial regression tested the associations between sociodemographic characteristics and the self-reported impact of COVID-19 on whether households had enough food to eat in 2020 only (0=Not at all, 1=A little, 2=A lot). \nResults: Approximately one-third of respondents lived in moderately or severely food insecure households between 2018 and 2020. The prevalence of living in severely food-insecure households was higher in 2019 compared to 2018 (OR:1.28; CI:1.061-1.540), and higher in 2019 compared to 2020 (OR: 1.17; CI: 0.97-1.41). Similarly, the proportion of respondents who reported preparing or consuming food collected from a food bank was greater in 2019 compared to 2018 (OR:1.49; CI:1.05-2.12) and greater in 2019 compared to 2020 (OR:1.13; CI:0.78-1.64). As hypothesized, respondents who were younger and who reported lower perceived income adequacy, lower levels of education, having a child under 18 years old, and who identified as Indigenous or Black had higher odds of living in food-insecure households. The associations between sociodemographics and household food insecurity were consistent over time, except for education and having a child. Respondents who had a child were less likely to live in a severely food-insecure household in 2019 (compared to 2018 and 2020), while those who did not have a child were more likely to live in a severely food-insecure household in 2019 (compared to 2018 and 2020). Respondents who had a university degree were more likely to live in moderately and severely food-insecure households in 2020 compared to 2019, while all other education groups had lower household food insecurity levels in 2020. When asked about the impact of the COVID-19 pandemic, about one-third of respondents self-reported that it had "a little" or "a lot" of impact on whether their household had enough food to eat. Low perceived income adequacy and self-reported financial impact of the pandemic were associated with self-reporting that the COVID-19 pandemic affected whether their household had enough food to eat. \nConclusion: The COVID-19 pandemic has been hypothesized as a potential contributor to food insecurity as it has altered the daily life and financial stability of many households in Canada. However, the findings suggest that household food insecurity decreased in 2020 following an increase in 2019. This research adds to the body of literature on household food insecurity during the first year of the COVID-19 pandemic. Future research should be conducted to examine how the prevalence of food insecurity continues to be impacted by the COVID-19 pandemic over time, especially as financial assistance programs created during the pandemic have ended, potentially impacting the income adequacy of households in Canada.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,052
Score d'incertitude au seuil0,375

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,008
Études des sciences et des technologies0,0050,001
Communication savante0,0030,001
Science ouverte0,0020,003
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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.

Tête enseignante Opus0,017
Tête enseignante GPT0,227
Écart entre enseignants0,210 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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