A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the multi-ethnic study of atherosclerosis and air pollution.
BACKGROUND
Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time.


OBJECTIVE
We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air).


METHODS
We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants' homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations.


RESULTS
Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92.


CONCLUSIONS
This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies.
Department of Biostatistics, and Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA.
Joshua P
JP
Keller
Casey
C
Olives
Sun-Young
SY
Kim
Lianne
L
Sheppard
Paul D
PD
Sampson
Adam A
AA
Szpiro
Assaf P
AP
Oron
Johan
J
Lindström
Sverre
S
Vedal
Joel D
JD
Kaufman
D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000032:analysis*; D050197:Atherosclerosis / Q000208:ethnology / Q000378:metabolism*; D002244:Carbon / Q000032:analysis; D004784:Environmental Monitoring / Q000379:methods*; D005006:Ethnicity; D006801:Humans; D008962:Models, Theoretical; D009589:Nitrogen Oxides / Q000032:analysis; D052638:Particulate Matter / Q000032:analysis; D062211:Spatio-Temporal Analysis; D014481:United States
D000393:Air Pollutants; D009589:Nitrogen Oxides; D052638:Particulate Matter; D002244:Carbon