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Enregistrement W4388850659 · doi:10.1111/resp.14624

Adaptation in real time: Wildfire smoke exposure and respiratory health

2023· article· en· W4388850659 sur OpenAlexafffundabout
Emily Brigham, Mary E. Crocker

Notice bibliographique

RevueRespirology · 2023
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueFire effects on ecosystems
Établissements canadiensVancouver Coastal Health Research InstituteUniversity of British ColumbiaVancouver Coastal Health
Organismes subventionnairesNational Institutes of HealthMichael Smith Health Research BCNational Institute of Environmental Health SciencesCanadian Institutes of Health ResearchWorkSafeBCUniversity of Washington
Mots-clésMedicineParticulatesEnvironmental healthSmokeAsthmaAir quality indexAir pollutionEcologyMeteorologyInternal medicineBiology

Résumé

récupéré en direct d'OpenAlex

Wildfires are increasing in frequency, intensity and area burned worldwide, fuelled in part by human-caused climate change.1, 2 Wildfire smoke (WFS) plumes, containing a complex mixture of airborne particulates, carbon monoxide and dioxide, nitrogen oxides, volatile organic compounds and other products of combustion, can travel thousands of miles3 and pose a threat to human health far from the site of the responsible fire (Figure 1). Fine particulate matter (PM2.5), a product of combustion processes more generally and present at high concentrations in WFS, is closely linked to health effects. WFS-attributed PM2.5 concentration is a commonly reported metric of WFS exposure, and in WFS-affected areas frequently exceeds recommended World Health Organization targets by more than 20-fold.4 Indeed, in some areas the rise in airborne particulates attributed to WFS has negated up to 50% of western US policy-related improvements in air quality over the last two decades.5 The short-term, negative health impacts of WFS are widely recognized. There is consistent evidence of association between WFS exposure and acute respiratory health outcomes, including respiratory infections, exacerbations of pre-existing asthma and chronic obstructive pulmonary disease, and related healthcare use.6 WFS exposure is also linked to all-cause mortality, and there is growing evidence for cardiovascular7 and other health effects.8 Effects are amplified in susceptible populations, including infants and children, pregnant people, the elderly, and those with pre-existing cardiac or respiratory conditions. Evidence is limited regarding the impact of long-term or repeated WFS exposure, potential delayed health effects, and the role of WFS exposure in the pathogenesis of diseases such as asthma or chronic obstructive pulmonary disease (COPD). Urgent investigation of these questions is warranted, as chronic exposure to PM2.5 from non-WFS pollutant sources has been causally linked to new-onset respiratory and cardiovascular disease, cancer, as well as increased mortality.9 Some evidence suggests that WFS-attributed PM2.5 may have exaggerated health impacts compared to other forms of PM2.5.10, 11 WFS is enriched with fine particles which have a high relative surface area to adsorb toxicants and chemicals.12 These particles can penetrate deep into the lung during respiration and translocate across the alveolar-capillary barrier, carrying adsorbed products directly into the bloodstream. Current data from in vitro, animal and human models suggest that PM2.5 exposure activates inflammation and oxidative stress pathways within the lung and systemically13; whether and how mechanistic pathways may differ by pollutant source, composition and co-pollutants is an area of active investigation. To address health impacts, there is critical need for drastic reduction in global fossil fuel emissions and parallel optimization of forest management. While these objectives are pursued, health interventions aim to limit WFS exposure. Individuals are encouraged to check and respond to their local air quality, primarily via air quality indices released by national public health or environmental agencies and incorporating PM2.5 data from government monitors (such as the US Air Quality Index and Canadian Air Quality Health Index). When air quality is poor based on these indices, remaining indoors is generally recommended, along with decreasing the indoor infiltration of outdoor air, using high efficiency particle air (HEPA) filtration and limiting indoor particle-producing activities (such as burning candles). If individuals are unable to make their own environment safe, or if there are other risks to safety (e.g., from co-exposure to extreme heat) they should ideally relocate either to publicly available spaces with cleaner air or to the home of a relative or friend with access to mitigation measures. During travel, individuals should use vehicle air filtration or N-95 respirators to reduce exposure. Aside from exposure mitigation measures such as these, there are no known interventions to prevent or alleviate the biologic impacts of WFS; development of such interventions represents an urgent need. Effective communication and operationalization of personal exposure reduction strategies is therefore critical. As with any public health measure, education on WFS mitigation requires coordinated effort at multiple levels, balancing consistency of messaging with unique individual needs and community context. Evidence supports a diverse messaging strategy using multiple communication streams and formats to relay consistent, evidence-informed guidance.14 Considerations include point of access (internet, social media, radio, television), content (language, complexity, graphics and resources) and frequency of release and updates. In addition, clinicians and health professionals are trusted sources of information and may provide individualized guidance where possible, and community organizations may also be empowered to complement this role. Individually-tailored strategies may be particularly important for those with higher susceptibility, lower educational attainment, or lack of resources, who would benefit from assistance overcoming barriers to implementing public health recommendations.15 Indeed, deployment of messaging and resources for optimized health during WFS events provides an opportunity to directly address health equity. Certain groups are at higher risk of exposure to WFS (vulnerable), including those with occupational exposures (e.g., wildland firefighters and other outdoor workers), individuals living near wildfire-prone regions, and those unable to modify their personal environment to mitigate exposure (e.g., due to housing, resource or social constraints). Prioritizing engagement with these individuals and communities at higher risk, along with dedication of resources, can help to reduce environmental health disparities. For example, efforts to increase the density of air quality monitoring stations in rural and/or underserved regions, many disproportionately impacted by WFS but lacking nearby monitoring, may improve the ability of communities to check and respond to conditions. Implementing these actions requires an equitable and nimble approach, with iterative adaptation of efforts to community context, values, preferences and emerging evidence. Coordinated messaging that makes use of diverse strategies at the individual, community and population level is needed in parallel to support for ongoing discovery and translation efforts. Success in these endeavours necessitates a cooperative effort among academic, government, industry and community leaders, with effective communication and knowledge-sharing across sectors. Fortifying resources among the most susceptible and/or vulnerable presents a pathway to environmental health equity and the highest level of health for all. Emily Brigham is supported by the National Institute for Environmental Health Sciences, award number K23ES029105, as well as a Michael Smith Health Research BC Health Professional-Investigator Award, and a Project Grant from the Canadian Institutes of Health Research. Mary Crocker is supported by the University of Washington Pediatric and Reproductive Environmental Health Scholars (UW PREHS) K12 program, National Institutes of Health (NIH) award number K12ES033584. Emily Brigham is past Chair of the Programming Committee of the Environmental, Occupational, and Population Health Programming Committee of the American Thoracic Society.

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)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
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 enseignants0,140
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
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)0,0000,001

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.

Tête enseignante Opus0,020
Tête enseignante GPT0,264
Écart entre enseignants0,244 · 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.

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

Citations2
Publié2023
Routes d'admission3
Résumé présentoui

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