Temperature and particulate matter as environmental factors associated with seasonality of influenza incidence - an approach using Earth observation-based modeling in a health insurance cohort study from Baden-Württemberg (Germany).


Journal

Environmental health : a global access science source
ISSN: 1476-069X
Titre abrégé: Environ Health
Pays: England
ID NLM: 101147645

Informations de publication

Date de publication:
16 12 2022
Historique:
received: 19 05 2022
accepted: 21 10 2022
entrez: 16 12 2022
pubmed: 17 12 2022
medline: 21 12 2022
Statut: epublish

Résumé

Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones. We examined influences of medium-term residential exposure to fine particulate matter (PM To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input. In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.

Sections du résumé

BACKGROUND
Influenza seasonality has been frequently studied, but its mechanisms are not clear. Urban in-situ studies have linked influenza to meteorological or pollutant stressors. Few studies have investigated rural and less polluted areas in temperate climate zones.
OBJECTIVES
We examined influences of medium-term residential exposure to fine particulate matter (PM
METHODS
To obtain complete spatial coverage of Baden-Württemberg, we modeled environmental exposure from data of the Copernicus Atmosphere Monitoring Service and of the Copernicus Climate Change Service. We computed spatiotemporal aggregates to reflect quarterly mean values at post-code level. Moreover, we prepared health insurance data to yield influenza incidence between January 2010 and December 2018. We used generalized additive models, with Gaussian Markov random field smoothers for spatial input, whilst using or not using quarter as temporal input.
RESULTS
In the 3.85 million cohort, 513,404 influenza cases occurred over the 9-year period, with 53.6% occurring in quarter 1 (January to March), and 10.2%, 9.4% and 26.8% in quarters 2, 3 and 4, respectively. Statistical modeling yielded highly significant effects of air temperature, precipitation, PM
CONCLUSIONS
Whilst strong statistical association of temperature with other stressors makes it difficult to distinguish between direct and mediated temperature effects, results confirm genuine effects by fine particulate matter on influenza infections for both rural and urban areas in a temperate climate. Future studies should attempt to further establish the mediating mechanisms to inform public health policies.

Identifiants

pubmed: 36527040
doi: 10.1186/s12940-022-00927-y
pii: 10.1186/s12940-022-00927-y
pmc: PMC9755806
doi:

Substances chimiques

Particulate Matter 0
Air Pollutants 0
Nitrogen Dioxide S7G510RUBH

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

131

Informations de copyright

© 2022. The Author(s).

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Auteurs

Jörn Rittweger (J)

Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany. joern.rittweger@dlr.de.
Department of Pediatrics and Adolescent Medicine, University Hospital Cologne, Cologne, Germany. joern.rittweger@dlr.de.

Lorenza Gilardi (L)

German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

Maxana Baltruweit (M)

Allgemeine Ortskrankenkasse Baden-Württemberg (AOK-BW), Stuttgart, Germany.

Simon Dally (S)

Allgemeine Ortskrankenkasse Baden-Württemberg (AOK-BW), Stuttgart, Germany.

Thilo Erbertseder (T)

German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

Uwe Mittag (U)

Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany.

Muhammad Naeem (M)

Kohat University of Science and Technology, Kohat, Pakistan.

Matthias Schmid (M)

Institute of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany.

Marie-Therese Schmitz (MT)

Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany.
Institute of Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany.

Sabine Wüst (S)

German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

Stefan Dech (S)

German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

Jens Jordan (J)

Institute of Aerospace Medicine, German Aerospace Center (DLR), 51147, Cologne, Germany.
Medical Faculty, University of Cologne, Cologne, Germany.

Tobias Antoni (T)

Allgemeine Ortskrankenkasse Baden-Württemberg (AOK-BW), Stuttgart, Germany.

Michael Bittner (M)

German Remote Sensing Data Center, German Aerospace Center (DLR), Oberpfaffenhofen, Germany.

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Classifications MeSH