Individual and Geospatial Determinants of Health Associated With School-Based Human Papillomavirus Immunization in Alberta: Population-Based Cohort Study
Notice bibliographique
Résumé
BACKGROUND: Human papillomavirus (HPV) infection causes nearly all cervical cancer cases and is a cause of anogenital and oropharyngeal cancers. The incidence of HPV-associated cancers is inequitable, with an increased burden on marginalized groups in high-income countries. Understanding how immunization status varies by material and social deprivation, health system, and geospatial factors is valuable for prioritizing and planning HPV immunization interventions. OBJECTIVE: The objective of this study was to describe school-based HPV immunization rates by individual and geospatial determinants of health in Alberta, Canada. METHODS: Health administrative data for male and female individuals born in 2004 in Alberta were used to determine HPV immunization status based on age and the number of doses administered in schools during the 2014/2015-2018/2019 school years. Immunization status and its relationship with material and social deprivation and health system factors were assessed by a logistic regression model. Geospatial clustering was assessed using Getis-Ord Gi* hot spot analysis. Mean scores of material and social deprivation and health system factors were compared between hot and cold spots without full HPV immunization using independent samples t tests. A multidisciplinary team comprising researchers and knowledge users formed a co-design team to design the study protocol and review the study results. RESULTS: The cohort consisted of 45,207 youths. In the adjusted model, the odds of those who did not see their general practitioner (GP) within 3 years before turning 10 years old and not being fully immunized were 1.965 times higher (95% CI 1.855-2.080) than those who did see their GP. The odds of health system users with health conditions and health system nonusers not being fully immunized were 1.092 (95% CI 1.006-1.185) and 1.831 (95% CI 1.678-1.998) times higher, respectively, than health system users without health conditions. The odds of those who lived in areas with the most material and social deprivation not being fully immunized were 1.287 (95% CI 1.200-1.381) and 1.099 (95% CI 1.029-1.174) times higher, respectively, than those who lived in areas with the least deprivation. The odds of those who lived in rural areas not being fully immunized were 1.428 times higher (95% CI 1.359-1.501) than those who lived in urban areas. Significant hot spot clusters of individuals without full HPV immunization exist in rural locations on the northern and eastern regions of Alberta. Hot spots had significantly worse mean material deprivation scores (P=.008) and fewer GP visits (P=.001) than cold spots. CONCLUSIONS: Findings suggest that material and social deprivation, health system access, and rural residency impact HPV immunization. Such factors should be considered by public health professionals in other jurisdictions and will be used by the Alberta co-design team when tailoring programs to increase HPV vaccine uptake in priority populations and regions.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 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) | 0,002 | 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 ».