Global and regional child deaths due to injuries: an assessment of the evidence
Notice bibliographique
Résumé
BACKGROUND: Injuries result in substantial number of deaths among children globally. The burden across many settings is largely unknown. We estimated global and regional child deaths due to injuries from publicly available evidence. METHODS: We searched for community-based studies and nationally representative data reporting on child injury deaths published after year 1990 from CINAHL, EMBASE, IndMed, LILACS, Global Health, MEDLINE, SCOPUS, and Web of Science. Specific and all-cause mortality due to injuries were extracted for three age groups (0-11 months, 1-4 years, and 0-4 years). We conducted random-effects meta-analysis on extracted crude estimates, and developed a meta-regression model to determine the number of deaths due to injuries among children aged 0-4 years globally and across the World Health Organization (WHO) regions. RESULTS: < 0.001) reflecting variable data sources and study designs. For children aged 0-11 months, the pooled crude injury mortality rate was 29.6 (95% confidence interval (CI) = 21.1-38.1) per 100 000 child population, with asphyxiation being the leading cause of death (neonatal) at 189.1 (95% CI = 142.7-235.4) per 100 000 followed by suffocation (post-neonatal) at 18.7 (95% CI = 11.8-25.7) per 100 000. Among children aged 1-4 years, the pooled crude injury mortality rate was 32.7 (95% CI = 27.3-38.1) per 100 000, with traffic injuries and drowning the leading causes of deaths at 10.8 (95% CI = 8.9-12.8) and 8.8 (95% CI = 7.5-10.2) per 100 000, respectively. Among children under five years, the pooled injury mortality rate was 37.7 (95% CI = 32.7-42.7) per 100 000, with traffic injuries and drowning also the leading causes of deaths at 10.3 (95% CI = 8.8-11.8) and 8.9 (95% CI = 7.8-9.9) per 100 000 respectively. When crude mortality changes over age, WHO regions, and study period were accounted for in our model, we estimated that in 2015 there were 522 167 (95% CI = 395 823-648 630) deaths among children aged 0-4 years, with South East Asia (SEARO) recording the highest number of deaths at 195 084 (95% CI = 159476-230502), closely followed by the Africa region (AFRO) with 176523 (95% CI = 115 040-237 831) deaths. Globally, traffic injuries and drowning were the leading causes of under-five injury fatalities in 2015 with 142 661 (22.0/100 000) and 123 270 (19.0/100 000) child deaths, respectively. The exception being burns in AFRO with 57 784 deaths (38.6/100 000). CONCLUSIONS: Varying study designs, case definitions, and particularly limited country representation from Africa and South-East Asia (where we reported higher estimates), imply a need for more studies for better population representative estimates. This study may have however provided improved understanding on child injury death profiles needed to guide further research, policy reforms and relevant strategies globally.
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 | 0,067 | 0,155 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,010 | 0,018 |
| Bibliométrie | 0,027 | 0,022 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 ».