Social Factors and Nutrition Risk in Community-Living Seniors During the COVID-19 Pandemic
Notice bibliographique
Résumé
Pandemic countermeasures (e.g., lockdown, restrictions) enacted to minimize the spread of COVID-19 may put older adults at nutrition risk. This thesis uses an online/telephone survey to investigate factors associated with nutrition risk for community-dwelling older adults living in Hamilton, Ontario, Canada during the COVID-19 pandemic. Data were collected on nutrition risk, loneliness, mental health, assistance with meal preparation and/or delivery, frequency of making phone/video calls and using social media, and more. Subsequent data were collected in waves approximately three months apart. Objectives of this thesis were to understand the prevalence of high nutrition risk and identify the association with social-related variables that could be impacted by COVID-19 during different time points of the pandemic. Research questions were: \n \n1. What is the prevalence of high nutrition risk (SCREEN-8 score <38) in the IMPACT sample? \n \n2. Are participant-reported variables (self-reported mental health, loneliness over the past week, and receiving assistance with meal preparation or delivery) that could be impacted by COVID-19 shelter-in-place public health policy in the first wave of the pandemic, associated with baseline nutrition risk scores (SCREEN-8) in community-dwelling adults over 65 years old in Hamilton, Ontario, when adjusting for meaningful covariates (e.g., sex, age)? \n \n3. Is there a change in median nutrition risk score over nine months in community-dwelling adults over 65 years old in Hamilton, Ontario? \n \n4. Do participants change nutrition risk categorization over this time frame? \n \n5. Are changes in mental health, loneliness, frequency of video/phone calls and use of social media associated with change in nutrition risk scores over time (from baseline to nine months)? \n \nFrom this sample of older adults (n=272, 78±7.3 years old, 70% female), we found that nutrition risk was prevalent among the community-dwelling older adults (64% at high risk). In a multivariable cross-sectional analysis that examined baseline only, loneliness in the past week (β -2.92, 95% CI [-5.51, -0.34]) and resilience (β 1.28, [0.04, 2.52]) were found to be associated with nutrition risk. In a second longitudinal analysis (n=178) based on a subset with a complete nutrition risk questionnaire nine months later, authors also found that frequency of direct social contacts from phone/video calls was associated with less nutrition risk (β -6.84, [-12.9, -0.77]), but people using more social media are more likely to be at high risk (β 6.19, [0.64, 11.75]). \n \nFindings from this thesis may inform public health interventions with respect to social interactions in pandemic circumstances or other challenging situations. This research also implies that it is critical to understand and advocate for healthy social media use to improve nutrition for older adults. Strategies to mitigate the adverse outcomes, such as loneliness and subsequent nutrition risk of future pandemic countermeasures should target this vulnerable group.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».