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

• Published in: Environmental health Vol. 13; no. 1; p. 2
• Main Authors: Kioumourtzoglou, Marianthi-Anna, Spiegelman, Donna, Szpiro, Adam A, Sheppard, Lianne, Kaufman, Joel D, Yanosky, Jeff D, Williams, Ronald, Laden, Francine, Hong, Biling, Suh, Helen
• Format: Journal Article
• Language: English
• Published: London BioMed Central 13.01.2014; BioMed Central Ltd
• Subjects: Air Pollutants - analysis; Air pollution; Bias; Calibration; Cities; Earth and Environmental Science; Environment; Environmental Exposure - analysis; Environmental Exposure - statistics & numerical data; Environmental Health; Environmental protection; Exposure; Health risk assessment; Health risks; Heterogeneity; Humans; Linear Models; Motor vehicles; Occupational Medicine/Industrial Medicine; Outdoor air quality; Particle Size; Particulate matter; Particulate Matter - analysis; Public Health; Research Design; Sulfates - analysis; Uncertainty; United States; United States; Cities; United States > US; Massachusetts; Monitoring data; Spatio-temporal models; Exposure measurement error; Fine particles; Fine particles of ambient origin
• ISSN: 1476-069X; 1476-069X
• DOI: 10.1186/1476-069X-13-2

Background Exposure measurement error is a concern in long-term PM 2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM 2.5 exposures from validation studies and typically available surrogate exposures. Methods Daily personal and ambient PM 2.5 , and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM 2.5 of ambient origin. Since PM 2.5 of ambient origin could only be determined for five cities, personal exposure to total PM 2.5 was also considered. Surrogate exposures were estimated as ambient PM 2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results When monthly-averaged personal PM 2.5 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 PM 2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM 2.5 , for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM 2.5 . Conclusions Calibration 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.