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Enregistrement W4402732979 · doi:10.1093/annweh/wxae073

A field investigation of 3 masks proposed as respiratory protection for wildland firefighters: a randomized controlled trial in British Columbia, Canada

2024· article· en· W4402732979 sur OpenAlexafffundabout
Natasha Broznitsky, Mona Shum, David W. Kinniburgh, Drew Lichty, Sylvia Tiu, Taryn Toic, Tanis Zadunayski, Nicola Cherry

Notice bibliographique

RevueAnnals of Work Exposures and Health · 2024
Typearticle
Langueen
DomaineHealth Professions
ThématiqueOccupational Health and Performance
Établissements canadiensUniversity of AlbertaUniversity of CalgaryInstitute of Indigenous Peoples' HealthGovernment of British Columbia
Organismes subventionnairesUniversity of Alberta
Mots-clésRespiratorPersonal protective equipmentEnvironmental scienceFirefightingParticulatesMedicineToxicologyChemistryCoronavirus disease 2019 (COVID-19)Internal medicine

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Wildland firefighters are exposed through the lungs and skin to particulate matter, fumes, and vapors containing polycyclic aromatic hydrocarbons (PAH). Wearing respiratory protection should reduce pulmonary exposure, but there is uncertainty about the most effective and acceptable type of mask. METHODS: Firefighters from 6 unit crews working with the British Columbia Wildfire Service were approached and those consenting were randomly allocated within each crew to a "no mask" control group or to use 1 of 3 types of masks: X, half-face respirator with P100/multi gas cartridge; Y, cloth with alpaca filter; Z mesh fabric with a carbon filter. Crews were followed for 3 consecutive firefighting days. The mask allocated was constant for each firefighter throughout. All participants completed a brief questionnaire at the start and end of each day, giving information on mask use, respiratory symptoms, and assessment of mask qualities. Spot urine samples were collected pre and post shift to assess 1-hydroxypyrene (1-HP) concentration as an indicator of total PAH absorption. Skin wipe samples from the hands and throat were collected pre and post shift and analyzed for PAH concentration. On each day monitored, 4 participants carried sampling pumps to measure total particulates and PAHs on particles and in vapor phase. The primary outcome was the concentration of urinary 1-HP at the end of the fire day. Secondary outcomes were changes in respiratory and eye symptoms during the course of the shift, reported mask use, and perception of mask qualities. The analysis used a 3-level random intercept regression model that clustered observations within individuals and crews. We aimed to detect any relation of allocated mask type to the 4 outcomes, having allowed for estimated exposure. RESULTS: Information was collected from 89 firefighters, including 14 women: 49% (37/75) of male firefighters were bearded. Nineteen fire days were monitored for a total of 263 firefighter × days, 64 to 68 for each intervention group. The end of shift 1-HP was higher than the start of the shift. Urinary 1-HP was more strongly related to PAHs on the skin than in the breathing zone. Men with beards had higher end-of-shift urinary log 1-HP/creat (ng/g) than other firefighters. None of the groups allocated a mask had lower 1-HP than the no-mask group, either in the study group overall or when stratified by beard-wearing. Among those without either beards or a failed fit-test, Mask Z reduced at the end of shift 1-HP where airborne PAH concentration was high. End-of-shift symptoms were related to particle mass in the breathing zone but was not mitigated by any of the masks. Hours electing not to wear a mask increased from the first to third shift for all mask types. Mask Z was rated as more comfortable than other types. Mask X was rated highest on fit and perceived protection. Mask Y gained the lowest ratings on fit, comfort and feelings of protection. CONCLUSIONS: Allocated masks did not provide protection overall, but the results highlighted the need for a wider understanding of the circumstances in which wearing efficient protection is well-advised.

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)0,004
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,133
Score d'incertitude au seuil0,828

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0040,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
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 Opus0,105
Tête enseignante GPT0,415
Écart entre enseignants0,310 · 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'étudeEssai randomisé
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

Citations6
Publié2024
Routes d'admission3
Résumé présentoui

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