Outbreak detection was performed with log-linear temporal adjustment.
Although maximum weighted traffic within 150 m was not associated with SAB in the analysis without the temporal adjustment, adjusting for NO2 levels during the first month of pregnancy increased the association between SAB and that traffic metric (Table 3).
The proposed method consists of four main steps: classification, motion-trace volume collection, temporal adjustment, and ANN prediction.
The temporal adjustment of LUR spatial estimates of pollutant levels assumed that the city spatial surface and the spatial distribution of pollutants remained constant over the study period.
In addition, temporal adjustment of LUR pollution surfaces using ambient monitoring station data may not be appropriate because of the unvalidated assumption that ambient monitoring site measures and LUR modeled concentrations co-vary over space.
A main strength of the study is the use of a fine-scale exposure assessment based on temporal adjustment of LUR in a multi-ethnic cohort with information on a range of potential confounders and additional measures of newborn size.
However, such temporal adjustment of LUR pollution surfaces may not be appropriate because of the un-validated assumption that ambient monitoring site measures and LUR modeled concentrations co-vary over space.
The difference between these estimates is not likely attributable to address changes, but mostly to the temporal adjustment from original LUR models to the time of the present investigation.
We cannot rule out the potential exposure misclassification that may have arisen from the lack of assessment of nonresidential exposures, from the lack of assessment of residential mobility during pregnancy, and from assumptions needed for the temporal adjustment of the LUR models.
We further applied the NO2 daily temporal adjustment to NOx and PM2.5 absorbance spatial estimates because of their high correlation (Cyrys et al. 2003).
We further applied the NOx daily temporal adjustment to PM2.5 absorbance spatial estimates because of their high correlation (Cyrys et al. 2003), and the PM10 daily temporal adjustment to PMcoarse and PM2.5 (Pedersen et al. 2013), to obtain the respective spatiotemporal estimates of exposure to air pollution, following the methodology in ESCAPE (2009).
