The impact of COVID-19 on the lives of Canadians with and without non-communicable chronic diseases: results from the iCARE Study
Notice bibliographique
Résumé
Abstract Background The COVID-19 pandemic and its prevention policies have taken a toll on Canadians, and certain subgroups may have been disproportionately affected, including those with non-communicable diseases (NCDs; e.g., heart and lung disease) due to their risk of COVID-19 complications and women due to excess domestic workload associated with traditional caregiver roles during the pandemic. Aims/Objectives We investigated the impacts of COVID-19 on mental health, lifestyle habits, and access to healthcare among Canadians with NCDs compared to those without, and the extent to which women with NCDs were disproportionately affected. Methods As part of the iCARE study ( www.icarestudy.com ), data from eight cross-sectional Canadian representative samples (total n = 24,028) was collected via online surveys between June 4, 2020 to February 2, 2022 and analyzed using general linear models. Results A total of 45.6% (n = 10,570) of survey respondents indicated having at least one physician-diagnosed NCD, the most common of which were hypertension (24.3%), chronic lung disease (13.3%) and diabetes (12.0%). In fully adjusted models, those with NCDs were 1.18–1.24 times more likely to report feeling lonely, irritable/frustrated, and angry ‘to a great extent’ compared to those without (p’s < 0.001). Similarly, those with NCDs were 1.22–1.24 times more likely to report worse eating and drinking habits and cancelling medical appointments/avoiding the emergency department compared to those without (p’s < 0.001). Moreover, although there were no sex differences in access to medical care, women with NCDs were more likely to report feeling anxious and depressed, and report drinking less alcohol, compared to men with NCDs (p’s < 0.01). Conclusion Results suggest that people with NCDs in general and women in general have been disproportionately more impacted by the pandemic, and that women with NCDs have suffered greater psychological distress (i.e., feeling anxious, depressed) compared to men, and men with NCDs reported having increased their alcohol consumption more since the start of COVID-19 compared to women. Findings point to potential intervention targets among people with NCDs (e.g., prioritizing access to medical care during a pandemic, increasing social support for this population and mental health support).
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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 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,038 | 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 ».