Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studiesReportar como inadecuado

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Environmental Health

, 13:2

First Online: 13 January 2014Received: 25 August 2013Accepted: 06 January 2014DOI: 10.1186-1476-069X-13-2

Cite this article as: Kioumourtzoglou, MA., Spiegelman, D., Szpiro, A.A. et al. Environ Health 2014 13: 2. doi:10.1186-1476-069X-13-2


BackgroundExposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures.

MethodsDaily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models.

ResultsWhen monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 95% CI:0.14, 0.47 for nearest monitor and 0.54 95% CI:0.42, 0.65 for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5.

ConclusionsCalibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies.

KeywordsExposure measurement error Fine particles Fine particles of ambient origin Monitoring data Spatio-temporal models AbbreviationsCHDCoronary heart disease

COPDChronic obstructive pulmonary disease

EPAEnvironmental protection agency

MIMyocardial infarction

PM2.5Fine particulate matter

SO 4 2 − Open image in new windowSulfate.

Electronic supplementary materialThe online version of this article doi:10.1186-1476-069X-13-2 contains supplementary material, which is available to authorized users.

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Autor: Marianthi-Anna Kioumourtzoglou - Donna Spiegelman - Adam A Szpiro - Lianne Sheppard - Joel D Kaufman - Jeff D Yanosky - R

Fuente: https://link.springer.com/

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