Unveiling the disparities between private and public preschools in the risk for pinworm infections in China: a multicentre cross-sectional study
Notice bibliographique
Résumé
BACKGROUND: In China, public preschools only admit children from local permanent resident families, differing from private preschools admitting children mostly from transient population families such as work migrants. Thus, this study aims to compare pinworm infection rate and its risk factors between private and public preschools to contribute to the limited understanding of the disparities. METHODS: A three-year cross-sectional study was conducted in Jiangsu Province, China from 2019 to 2021. In each study site, two preschools types were selected: private preschool and public preschool. Multi-stage cluster sampling was applied. The study sites, preschools, and classes were selected based on convenience and cooperation. The calculated sample size for each preschool was 229. Participants were expected to proportionally distributed across the lower, the middle, and the upper grade to balance the age bracket. Questionnaire surveys were administered to parents with teachers' help. One adhesive cellophane tape swab sample was collected by local health workers from children in the morning at preschool. Single factor and multiple backward logistic regression analysis were conducted to identify the risk factors for pinworm infections. RESULTS: This study enrolled 3678, 2568, and 2529 preschool children in 2019, 2020, and 2021, respectively. The three-year pooled infection rate was 0.88% (1.46% for private preschool and 0.18% for public preschool). The pinworm infection rates were statistically higher in private preschool children than in public preschool children (2.07% vs. 0.24% in 2019, P-value < 0.001; 0.82% vs. 0.08% in 2020, P-value = 0.014; 1.22% vs. 0.19% in 2021, P-value = 0.008; respectively). Private preschool was a risk factor for pinworm infection (OR = 6.534, 95%CI = 2.523-22.336). Older age and worse hygiene habit were risk factors among private preschool children (OR = 1.476, 95%CI = 1.152-1.911; OR = 1.311, 95%CI = 1.053-1.606). Among public preschool children, a medium or higher family income level was a protective factor for pinworm infection (OR = 0.081, 95%CI = 0.011-0.413). CONCLUSION: The results indicate that private preschool with children mostly from transient population should be prioritized for pinworm control. It is valuable for policymakers and health staff aiming to improve sanitation and reduce pinworm infections.
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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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».