Spatial and temporal estimation of air pollutants in New York City: exposure assignment for use in a birth outcomes study

BACKGROUND: Recent epidemiological studies have examined the associations between air pollution and birth outcomes. Regulatory air quality monitors often used in these studies, however, were spatially sparse and unable to capture relevant within-city variation in exposure during pregnancy. METHODS: This study developed two-week average exposure estimates for fine particles (PM(2.5)) and nitrogen dioxide (NO(2)) during pregnancy for 274,996 New York City births in 2008–2010. The two-week average exposures were constructed by first developing land use regression (LUR) models of spatial variation in annual average PM(2.5) and NO(2) data from 150 locations in the New York City Community Air Survey and emissions source data near monitors. The annual average concentrations from the spatial models were adjusted to account for city-wide temporal trends using time series derived from regulatory monitors. Models were developed using Year 1 data and validated using Year 2 data. Two-week average exposures were then estimated for three buffers of maternal address and were averaged into the last six weeks, the trimesters, and the entire period of gestation. We characterized temporal variation of exposure estimates, correlation between PM(2.5) and NO(2), and correlation of exposures across trimesters. RESULTS: The LUR models of average annual concentrations explained a substantial amount of the spatial variation (R(2) = 0.79 for PM(2.5) and 0.80 for NO(2)). In the validation, predictions of Year 2 two-week average concentrations showed strong agreement with measured concentrations (R(2) = 0.83 for PM(2.5) and 0.79 for NO(2)). PM(2.5) exhibited greater temporal variation than NO(2). The relative contribution of temporal vs. spatial variation in the estimated exposures varied by time window. The differing seasonal cycle of these pollutants (bi-annual for PM(2.5) and annual for NO(2)) resulted in different patterns of correlations in the estimated exposures across trimesters. The three levels of spatial buffer did not make a substantive difference in estimated exposures. CONCLUSIONS: The combination of spatially resolved monitoring data, LUR models and temporal adjustment using regulatory monitoring data yielded exposure estimates for PM(2.5) and NO(2) that performed well in validation tests. The interaction between seasonality of air pollution and exposure intervals during pregnancy needs to be considered in future studies.