We estimated 6-30% increases in odds of preterm birth per inter-quartile range increase in entire pregnancy exposures to OC, EC, benzene, PAHs, and diesel, biomass burning and ammonium nitrate PM2.5. These pollutants were positively correlated, underscored by their loading on a common factor, and had higher concentrations in winter than summer and inland compared to the coastal areas.
Our results for entire pregnancy averages appeared strongly driven by coastal versus non-coastal regional patterns in pollutant concentrations, with positive associations observed for pollutants with higher concentrations inland, and negative associations observed for pollutants with higher concentrations in coastal areas (vanadium, residual oil PM2.5 and CO). However, in multi-pollutant models (Table 4), positive associations for vanadium, residual oil PM2.5 and CO emerged, suggesting negative associations from single pollutant models reflected spatial (coastal versus non-coastal) and, to a lesser extent, temporal (winter versus summer) correlations. Positive associations we observed for the "non-coastal" pollutants in single pollutant models persisted in multi-pollutant models, indicating results were not purely driven by inland versus coastal comparisons, possibly due to risk factors for preterm birth other than air pollution that were not included in our analyses.
The negative associations estimated for geological and ammonium sulfate PM2.5 in multi-pollutant models may reflect the influence of meteorological factors with more favorable mixing and dispersion conditions for the other pollutants (e.g., levels of geological PM2.5 increase during higher wind conditions ) or may reflect negative correlations with pollutants like diesel PM2.5 and total PAHs that we were unable to adequately disentangle using this dataset and conventional logistic regression methods. Positive associations for entire pregnancy exposures to sea salt PM2.5 were closer to the null in multi-pollutant models.
We estimated 3-4% increases in odds of preterm birth per IQR increases in unseasonalized (annual average) LUR measures of NO, NO2 and NOx. Estimated associations between preterm birth odds and seasonalized LUR measures for the entire pregnancy period were null in single pollutant models, but became positive, and similar in magnitude to unseasonalized LUR measures, in multi-pollutant models. Associations between entire pregnancy averages of pollutants based on ambient monitoring data (PAHs, EC, OC, benzene, and diesel, biomass burning, and ammonium nitrate PM2.5) were greater in magnitude than those for the LUR exposure measures (based on IQR comparisons). This may reflect better representation of temporal and/or regional patterns in pollutant concentrations in the monitoring-based versus LUR measures. However, both types of metrics may be imperfect markers of the causal pollutants of interest. The LUR models were built on neighborhood-level NO, NO2 and NOx concentrations due to the relative ease of measurement with passive monitors deployed at many locations simultaneously; however, only two measurement periods were utilized to develop the models and it is still unclear how well NO, NO2 and NOx concentrations represent PAH concentrations at a local, neighborhood level. PAH concentrations have strong spatial and temporal variations in the LA Basin . We used ambient monitoring station data to incorporate temporal variability due to meteorology into the seasonalized LUR measures. 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. Collection of a suite of air toxics including PAHs on a neighborhood scale and multiple times over a year, would help further examine the importance of local versus regional traffic pollutant exposure, but would be expensive and logistically difficult to implement.
Inter-quartile range increases in entire pregnancy PAH averages were associated most strongly with preterm birth risk. However, PAH data were only collected at two stations (West Long Beach and Downtown Los Angeles) from December 2004 through the end of March 2006. Compared to all women living within 5 miles of a MATES station, preterm cases and controls with entire pregnancy PAH averages available were slightly more likely to be foreign-born and to use government programs for health care (see additional file 1: Table S-3) and less likely to be in the highest SES quintiles, which may further limit generalizability of our PAH results.
We did not observe associations between entire pregnancy averages of NO, NO2, NOx, and PM10 based on government monitors and preterm birth, while in single pollutant models, CO and PM2.5 were negatively associated and O3 slightly positively associated with this outcome (additional file 1: Table S-6). However, in multi-pollutant models, associations for entire pregnancy CO and PM2.5 became positive, while the association for O3 became null. In pregnancy period analyses, positive associations were observed for last pregnancy month increases in CO, NO, NO2, NOx and PM2.5, suggesting the importance of temporal patterns in pollution concentrations for this outcome. These associations were observed despite the more limited spatial information available for the criteria pollutants (only 4 of 7 MATES monitors measured criteria pollutants and for the other three stations we relied on other, more distant stations within five miles). Despite differences in study areas, designs, populations, and time periods, these latest results for the criteria pollutants are similar to those reported in our previous studies. For example, in Wilhelm and Ritz  we reported odds ratio point estimates ranging between 1.01 and 1.08 per 1 ppm increase in CO (depending on pregnancy period and how close women lived to ambient monitoring stations), while here we estimated an OR of 1.04 per 0.38 ppm increase in entire pregnancy CO in multi-pollutant models. Wu et al.  reported an OR of 1.06 per 5.65 ppb increase in entire pregnancy NOx as estimated by an air dispersion model (CALINE) while here we estimated an OR of 1.03 per 11.5 ppb increase in unseasonalized LUR NOx. However, the CALINE model only included traffic emissions within 3000 m of women's residences while the LUR model included traffic parameters within 11,000 m and the two studies included very different geographical areas within the vast and complex LA metropolitan area (South LA/port areas and Orange County versus LA County coastal, urban core and eastern valley areas).
Oxidative stress caused by exposure to particles and associated toxics is one potential biological pathway of interest for air pollution's influence on preterm birth. Organic components of particulate matter, which comprise a large proportion of freshly emitted exhaust and secondary aerosols, can induce cytokine and chemokine expression in respiratory epithelium possibly due to cytotoxic reactive oxygen species (ROS) generated by PAHs, metals and related compounds; these inflammatory and oxidant stress responses are expected to occur at extrapulmonary sites as well [47, 48]. Ultrafine particles in LA induced cellular heme oxygenase-1 expression and depleted intracellular glutathione, both important in oxidant stress responses, and were also shown to localize in mitochondria where they induce major structural damage which may also contributive to oxidative stress . Cho et al.  reported the highest in vitro ROS formation in the UFP mode in LA Basin particles and a relatively high correlation of redox activity with elemental carbon (r2 = 0.79), organic carbon (r2 = 0.53) and benzo(g, h, i)perylene (r2 = 0.82). Thus, a potential biologic mechanism through which UFPs and PAHs could exhibit their influence on adverse birth outcomes is through acting on oxidative stress and inflammatory pathways during pregnancy.
One limitation of this study was the relatively short time period (22 months) for which air toxics and speciated PM2.5 monitoring data were available. Because of seasonal fluctuations in air pollution concentrations within a given year (for example, ambient measures of NO and NOx and total PAHs exhibited strong seasonal variability with peaks in winter, while O3 and ammonium sulfate followed an opposite pattern with summer peaks) and because the number of births with available exposure measures was not equal across months in the study, there were moderate to strong negative correlations between first trimester and last pregnancy month exposure measures for many of the pollutants we evaluated. Second trimester exposure averages were highly positively correlated with entire pregnancy averages. These patterns limited our ability to identify pregnancy periods with greater susceptibility.
We used the SCAQMD's MATES III study results to estimate pregnancy period exposures to source-specific PM2.5 concentrations (diesel, gasoline, etc.). SCAQMD  provides a discussion of their data collection and source apportionment modeling methods. Because PM2.5 samples were composited for speciation analyses, only monthly-average source-specific PM2.5 values were available to derive pregnancy averages, thus temporal variation may not be well-represented. Here we used the CMB results based on the Northern Front Range Air Quality Study gasoline profile, as recommended by the SCAQMD, instead of CMB results based on the Department of Energy's Gasoline/Diesel Split Study gasoline profile . Although we did not observe positive associations between entire pregnancy averages of gasoline PM2.5 and preterm birth, we estimated a 5% increase in odds per 0.5 μg/m3 increase in second trimester exposure, similar to diesel PM2.5 effect estimates.
Because we relied on information recorded on California birth certificates for this study, we were unable to adjust for a number of potential confounding factors including active and passive smoking during pregnancy. In a previous population-based study incorporating survey data , we reported air pollution effect estimates for preterm birth adjusted for birth certificate variables (maternal age, education, race/ethnicity, and parity) did not change appreciably when we additionally adjusted for active or passive smoking or family income. Additionally, our population was predominately Hispanic (76%), with 68% of these mothers born outside the U.S. (54% in Mexico, 14% in other countries), and prenatal smoking rates among this group are low . Our air pollution effect estimates did not change appreciably when we adjusted for prenatal care initiation, payment source for prenatal care, or for a Census-based measure of SES at the block group level.
For this study we used a risk set approach, matching preterm cases to controls based on gestational age at birth. This ensured each exposure period evaluated was the same length and covered the same developmental stages for cases and controls. Also, entire pregnancy averages for controls did not include exposures after 37 completed weeks of gestation when controls, by definition, are no longer at risk of becoming cases . Matching on gestational age at birth versus birth date allowed us to maintain both spatial and temporal differences in air pollution exposures, a strength of our study.
A major strength of this study was the use of novel air pollution exposure information in addition to routine, government monitoring station data for criteria pollutants, which has so far been the predominant method of exposure assessment in birth outcome studies. By using PAH monitoring data in concert with source-specific PM2.5 information from a CMB model, we detected positive associations between prenatal exposure to PAHs and odds of preterm birth and our results suggest PM2.5 from diesel combustion may be a particularly important exposure source, but not necessarily the only exposure source of interest (we also observed associations with biomass burning PM2.5, and to a lesser extent, meat cooking PM2.5, other PAH sources). Associations with ammonium nitrate PM2.5 suggest secondary pollutant formation through atmospheric reactions may be important for this outcome. Altogether, the air pollution exposure measures used here allowed us to better pinpoint sources and pollutants (PAHs) as targets of future analyses. Additional studies utilizing air toxics in addition to criteria pollutant data and source-specific information on pollutant contributions would provide further evidence on how and which air pollutants impact fetal development and may help inform regulatory policy decisions.