Sources of PM 2.5 exposure misclassification in three Finnish register-based study populations and the impact on attenuation of health effect estimates.

Autor: Korhonen A; Department of Health Security, Finnish Institute for Health and Welfare (THL), P.O. Box 95, 70701 Kuopio, Finland; Department of Environmental and Biological Sciences, University of Eastern Finland (UEF), P.O. Box 1627, 70701 Kuopio, Finland. Electronic address: antti.korhonen@thl.fi., Rumrich IK; Department of Health Security, Finnish Institute for Health and Welfare (THL), P.O. Box 95, 70701 Kuopio, Finland; School of Pharmacy, University of Eastern Finland (UEF), P.O. Box 1627, 70211 Kuopio, Finland., Roponen M; Department of Environmental and Biological Sciences, University of Eastern Finland (UEF), P.O. Box 1627, 70701 Kuopio, Finland., Frohn LM; Department of Environmental Science, Aarhus University (AU), Frederiksborgvej 399, 4000 Roskilde, Denmark., Geels C; Department of Environmental Science, Aarhus University (AU), Frederiksborgvej 399, 4000 Roskilde, Denmark., Brandt J; Department of Environmental Science, Aarhus University (AU), Frederiksborgvej 399, 4000 Roskilde, Denmark., Tolppanen AM; School of Pharmacy, University of Eastern Finland (UEF), P.O. Box 1627, 70211 Kuopio, Finland., Hänninen O; Department of Health Security, Finnish Institute for Health and Welfare (THL), P.O. Box 95, 70701 Kuopio, Finland.
Jazyk: angličtina
Zdroj: The Science of the total environment [Sci Total Environ] 2024 Dec 01; Vol. 954, pp. 176422. Date of Electronic Publication: 2024 Sep 19.
DOI: 10.1016/j.scitotenv.2024.176422
Abstrakt: Air pollution is a leading environmental health risk factor. The risk estimates, primarily based on air pollution epidemiology, are sensitive to exposure misclassification, which can result in underestimation. To address some of these challenges, our aim is to investigate how the length of the period over which the exposure is averaged, trends in long-term PM 2.5 concentrations, and the seasonal variability are associated with each other. Furthermore, we assess the impact of residential relocation on exposure levels and quantify random exposure misclassification due to modelling and its impact on the attenuation of effects with respect to averaging time. We used nested air quality modelling across Finland, gridded population, and address histories from three study populations: the MATEX pregnancy and preschool children cohorts, as well as the FINPARK study's individuals diagnosed with Parkinson's disease and their controls, to estimate PM 2.5 exposures. The prediction error was estimated by comparing modelled concentrations to observations and by using previous estimates for random monitoring instrument error. Due to the decreasing trend in PM 2.5 concentrations, exposure levels rose progressively with longer averaging times, increasing by up to 28 % over a 16-year period. The shorter the exposure period, the more pronounced the seasonal effects: pregnant mothers' trimester-specific exposures were 13-22 % higher for trimesters ending in spring and 10-16 % lower for those ending in autumn compared to the average for the entire pregnancy. Residential relocation had a relatively minor impact on the exposure levels of the preschool children and adult FINPARK study population, but this effect was possibly partly masked by the decreasing trend. The results indicated that using predicted concentrations led to random exposure misclassification and potentially attenuated health effects. This effect became more notable when increasing the length of the exposure period from 3 months to 5 years, doubling the underestimation ratio from 1.5 to 3.1.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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