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Enregistrement W4415756938 · doi:10.1016/j.eclinm.2025.103580

Global, regional and national estimates of the burden of childhood asthma attributable to NO2 exposure for 204 countries and territories from 1990 to 2023: a Global Burden of Disease study 2023

2025· article· en· W4415756938 sur OpenAlexaff
Katrin Burkart, Sarah Wozniak, Susan C. Anenberg, Ana Antoranz Pereda, Nora M. Gilbertson, Charlie Ashbaugh, Daniel L. Goldberg, Perry Hystad, Gaige Hunter Kerr, Susan A. McLaughlin, Arash Mohegh, Michael Bräuer

Notice bibliographique

RevueEClinicalMedicine · 2025
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueAir Quality and Health Impacts
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesNational Institute of Environmental Health SciencesNational Oceanic and Atmospheric AdministrationNuclear Safety and Security CommissionWellcome TrustGeorge Washington UniversityCalifornia Air Resources BoardBill and Melinda Gates FoundationHealth Effects InstituteNational Aeronautics and Space AdministrationU.S. Environmental Protection AgencyU.S. Department of JusticeNational Institutes of HealthNational Science Foundation
Mots-clésBurden of diseaseAgency (philosophy)Disease burdenAsthmaDiseaseFunding AgencyBaseline (sea)

Résumé

récupéré en direct d'OpenAlex

<h2>Summary</h2><h3>Background</h3> Asthma, a chronic lung condition characterised by inflammation and airway constriction, has been associated with nitrogen dioxide (NO<sub>2</sub>) exposure, an association that particularly impacts children. Our study rigorously assessed this relationship and estimated the global burden of childhood asthma attributable to NO<sub>2</sub> exposure in 204 countries and territories from 1990 to 2023. <h3>Methods</h3> We systematically reviewed epidemiological studies evaluating NO<sub>2</sub>'s long-term impact on childhood asthma. Using burden of proof meta-regression methods that account for bias by adjusting for study-design covariates and quantify remaining unexplained between-study heterogeneity to incorporate into uncertainty, we estimated the relative risk of childhood asthma occurring as a function of NO<sub>2</sub> exposure. From this, we computed global and country-specific population attributable fractions (PAFs) – i.e., the proportional change in asthma risk that would occur if NO<sub>2</sub> exposure were reduced to a theoretical minimum exposure level range of 4.6–6.2 ppb. We applied PAFs to data from the 2023 Global Burden of Disease Study (GBD) to derive the asthma burden attributable to NO<sub>2</sub> exposure in children and youths under 20 years old. Burden of proof methods allowed us to further compute risk–outcome metrics quantifying the magnitude of the NO<sub>2</sub>–asthma association and its strength of supporting evidence. <h3>Findings</h3> We identified a total of 27 cohort studies, spanning 12 countries, primarily in Europe and high-income North America, with some studies from Asia (China and Japan). A meta-regression log-linear risk curve of these studies produced a summary RR of 1.05 (95% UI 0.99–1.12) per 5 ppb NO<sub>2</sub> and Egger's regression indicated significant publication bias. We estimated a global PAF of 4.67% (95% uncertainty interval [UI]: −3.75 to 20.6; all UIs reported in this study are inclusive of between-study heterogeneity except where noted), yielding 233,000 (−250,000–956,000) years lived with disability (YLDs) attributable to NO<sub>2</sub> globally in 2023. GBD 2023 ranked NO<sub>2</sub> seventh among environmental risk factors contributing to YLDs in children for all causes and third for childhood asthma YLDs. Attributable burden estimates and trends varied significantly by GBD super-region. While NO<sub>2</sub>-attributable childhood asthma burden has declined substantially since 1990 in the high-income and central Europe, eastern Europe, and central Asia super-regions, NO<sub>2</sub> remains a prominent environmental risk factor in these two super-regions, ranked third in both super-regions for paediatric asthma YLDs in 2023, contributing 57,100 (−63 600 to 242,000) and 6570 (−7050 to 30,200) YLDs, respectively. In South Asia, NO<sub>2</sub> ranks second as risk factor for pediatric asthma contributing to 20,100 (−17 600, 105,000) YLDs in 2023. <h3>Interpretation</h3> NO<sub>2</sub> pollution remains a top environmental risk for paediatric health, necessitating policy interventions targeting NO<sub>2</sub> pollution, especially in high-income locations and urban areas. <h3>Funding</h3> The research described in this article was conducted in part under contract with the Health Effects Institute (HEI), an organization jointly funded by the United States Environmental Protection Agency (EPA) and certain motor vehicle and engine manufacturers, grant number 4977/20-11. The contents of this article do not necessarily reflect the views of HEI or its sponsors, nor do they necessarily reflect the views and policies of the EPA or motor vehicle and engine manufacturers. Additional funding for this study was received by the Gates foundation, grant no. OPP1152504 for MB, KB, and SW. SA, DG, AM and GHK were supported by NASA grant no. 80NSSC21K0511 and SA and GHK NIH grant no. P20ES036775.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,062
Score d'incertitude au seuil0,998

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,032
Tête enseignante GPT0,364
Écart entre enseignants0,333 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2025
Routes d'admission1
Résumé présentoui

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