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The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction

BACKGROUND: Long-term exposure to particulate matter less than 2.5 μm in diameter (PM(2.5)) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these...

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Autores principales: Hart, Jaime E, Liao, Xiaomei, Hong, Biling, Puett, Robin C, Yanosky, Jeff D, Suh, Helen, Kioumourtzoglou, Marianthi-Anna, Spiegelman, Donna, Laden, Francine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427963/
https://www.ncbi.nlm.nih.gov/pubmed/25926123
http://dx.doi.org/10.1186/s12940-015-0027-6
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author Hart, Jaime E
Liao, Xiaomei
Hong, Biling
Puett, Robin C
Yanosky, Jeff D
Suh, Helen
Kioumourtzoglou, Marianthi-Anna
Spiegelman, Donna
Laden, Francine
author_facet Hart, Jaime E
Liao, Xiaomei
Hong, Biling
Puett, Robin C
Yanosky, Jeff D
Suh, Helen
Kioumourtzoglou, Marianthi-Anna
Spiegelman, Donna
Laden, Francine
author_sort Hart, Jaime E
collection PubMed
description BACKGROUND: Long-term exposure to particulate matter less than 2.5 μm in diameter (PM(2.5)) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these studies are subject to measurement error. However, to date, no study has attempted to incorporate adjustment for measurement error into a long-term study of the effects of air pollution on mortality. METHODS: We followed 108,767 members of the Nurses’ Health Study (NHS) 2000–2006 and identified all deaths. Biennial mailed questionnaires provided a detailed residential address history and updated information on potential confounders. Time-varying average PM(2.5) in the previous 12-months was assigned based on residential address and was predicted from either spatio-temporal prediction models or as concentrations measured at the nearest USEPA monitor. Information on the relationships of personal exposure to PM(2.5) of ambient origin with spatio-temporal predicted and nearest monitor PM(2.5) was available from five previous validation studies. Time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 percent confidence intervals (95%CI) for each 10 μg/m(3) increase in PM(2.5). Risk-set regression calibration was used to adjust estimates for measurement error. RESULTS: Increasing exposure to PM(2.5) was associated with an increased risk of mortality, and results were similar regardless of the method chosen for exposure assessment. Specifically, the multivariable adjusted HRs for each 10 μg/m(3) increase in 12-month average PM(2.5) from spatio-temporal prediction models were 1.13 (95%CI:1.05, 1.22) and 1.12 (95%CI:1.05, 1.21) for concentrations at the nearest EPA monitoring location. Adjustment for measurement error increased the magnitude of the HRs 4-10% and led to wider CIs (HR = 1.18; 95%CI: 1.02, 1.36 for each 10 μg/m(3) increase in PM(2.5) from the spatio-temporal models and HR = 1.22; 95%CI: 1.02, 1.45 from the nearest monitor estimates). CONCLUSIONS: These findings support the large body of literature on the adverse effects of PM(2.5), and suggest that adjustment for measurement error be considered in future studies where possible.
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spelling pubmed-44279632015-05-13 The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction Hart, Jaime E Liao, Xiaomei Hong, Biling Puett, Robin C Yanosky, Jeff D Suh, Helen Kioumourtzoglou, Marianthi-Anna Spiegelman, Donna Laden, Francine Environ Health Research BACKGROUND: Long-term exposure to particulate matter less than 2.5 μm in diameter (PM(2.5)) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these studies are subject to measurement error. However, to date, no study has attempted to incorporate adjustment for measurement error into a long-term study of the effects of air pollution on mortality. METHODS: We followed 108,767 members of the Nurses’ Health Study (NHS) 2000–2006 and identified all deaths. Biennial mailed questionnaires provided a detailed residential address history and updated information on potential confounders. Time-varying average PM(2.5) in the previous 12-months was assigned based on residential address and was predicted from either spatio-temporal prediction models or as concentrations measured at the nearest USEPA monitor. Information on the relationships of personal exposure to PM(2.5) of ambient origin with spatio-temporal predicted and nearest monitor PM(2.5) was available from five previous validation studies. Time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 percent confidence intervals (95%CI) for each 10 μg/m(3) increase in PM(2.5). Risk-set regression calibration was used to adjust estimates for measurement error. RESULTS: Increasing exposure to PM(2.5) was associated with an increased risk of mortality, and results were similar regardless of the method chosen for exposure assessment. Specifically, the multivariable adjusted HRs for each 10 μg/m(3) increase in 12-month average PM(2.5) from spatio-temporal prediction models were 1.13 (95%CI:1.05, 1.22) and 1.12 (95%CI:1.05, 1.21) for concentrations at the nearest EPA monitoring location. Adjustment for measurement error increased the magnitude of the HRs 4-10% and led to wider CIs (HR = 1.18; 95%CI: 1.02, 1.36 for each 10 μg/m(3) increase in PM(2.5) from the spatio-temporal models and HR = 1.22; 95%CI: 1.02, 1.45 from the nearest monitor estimates). CONCLUSIONS: These findings support the large body of literature on the adverse effects of PM(2.5), and suggest that adjustment for measurement error be considered in future studies where possible. BioMed Central 2015-05-01 /pmc/articles/PMC4427963/ /pubmed/25926123 http://dx.doi.org/10.1186/s12940-015-0027-6 Text en © Hart et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Hart, Jaime E
Liao, Xiaomei
Hong, Biling
Puett, Robin C
Yanosky, Jeff D
Suh, Helen
Kioumourtzoglou, Marianthi-Anna
Spiegelman, Donna
Laden, Francine
The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction
title The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction
title_full The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction
title_fullStr The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction
title_full_unstemmed The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction
title_short The association of long-term exposure to PM(2.5) on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction
title_sort association of long-term exposure to pm(2.5) on all-cause mortality in the nurses’ health study and the impact of measurement-error correction
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4427963/
https://www.ncbi.nlm.nih.gov/pubmed/25926123
http://dx.doi.org/10.1186/s12940-015-0027-6
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