88 Association between area level material deprivation and incidence of hospitalization among children with SARS-CoV-2 in Montreal
Notice bibliographique
Résumé
Abstract Background Although sociodemographic factors have been linked with SARS-CoV-2 infection and hospitalizations in adults, there are little data on the association between sociodemographic characteristics and SARS-CoV-2-related hospitalization in children. Objectives The objective of this study was to determine the association between area-level material deprivation and incidence of hospitalization with SARS-CoV-2 among children. Design/Methods We conducted a retrospective cohort study of all children (0-17 years of age) with a PCR-confirmed SARS-CoV-2 infection between March 1, 2020, and May 31, 2021, at a tertiary care pediatric hospital. Data were collected through chart review and included age, sex, and postal code. Postal codes were then assigned a dissemination area-level material deprivation score, measured via the Pampalon Material Deprivation Index (PMDI) quintiles. The Pampalon Material Deprivation Index (PMDI) uses postal codes to describe factors related to material deprivation obtained from the Canadian census, which are proxies for individual data in a geographic area. Specifically, the PMDI integrates data regarding (i) the proportion of persons without a high school diploma; (ii) the employment-to-population ratio; (iii) average personal income which is aggregated at the dissemination area level. We examined the association between PMDI quintiles and hospitalization using Poisson regression. Results During the study period, 964 children had a positive PCR-confirmed SARS-CoV-2 test and 124 were hospitalized due to SARS-CoV-2 infection. Children from the most deprived PMDI quintile represented 31.6% of positive cases and 40.7% of hospitalizations (Figure 1 and 2). Both in bivariate and multivariable regression analyses, there was evidence of greater proportion of positive test results in the most deprived PMDI quintile (Quintile 5) compared to the least deprived quintile (Quintile 1) (rate ratio 1.77, 95%CI: 1.36; 2.62) (Table 1). The incidence of hospitalization due to SARS-CoV-2 infection was 2.42 times greater in the most deprived quintile compared to the least deprived quintile (95%CI: 1.33; 4.41) (table 1). In a post-hoc analysis, the risk for severe disease appeared higher for children living in Q5 areas relative to other areas but the difference did not reach statistical significance. Conclusion In conclusion, in this study we found evidence that Canadian children living in neighbourhoods with high material deprivation had a higher incidence of infection and hospitalizations related to SARS-Cov-2 compared to children living in neighbourhoods with less material deprivation. Public health authorities should take these disparities into account when devising public health policy and interventions especially at this crucial point in the pandemic. Special efforts should be deployed to protect children from these more disadvantaged areas, especially as vaccination is not yet available to a majority of children.
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 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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».