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The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment.

ABSTRACT: Several papers reported associations between airborne fine particulate matter (PM2.5) and birth weight, though findings are inconsistent across studies. Conflicting results might be due to (1) different PM2.5 chemical structure across locations, and (2) various exposure assignment methods across studies even among the studies that use ambient monitors to assess exposure. We investigated associations between birth weight and PM2.5 chemical constituents, considering issues arising from choice of buffer size (i.e. distance between residence and pollution monitor). We estimated the association between each pollutant and term birth weight applying buffers of 5 to 30km in Connecticut (2000-2006), in the New England region of the U.S. We also investigated the implication of the choice of buffer size in relation to population characteristics, such as socioeconomic status. Results indicate that some PM2.5 chemical constituents, such as nitrate, are associated with lower birth weight and appear more harmful than other constituents. However, associations vary with buffer size and the implications of different buffer sizes may differ by pollutant. A homogeneous pollutant level within a certain distance is a common assumption in many environmental epidemiology studies, but the validity of this assumption may vary by pollutant. Furthermore, we found that areas close to monitors reflect more minority and lower socio-economic populations, which implies that different exposure approaches may result in different types of study populations. Our findings demonstrate that choosing an exposure method involves key tradeoffs of the impacts of exposure misclassification, sample size, and population characteristics.

SUBMITTER: Ebisu K

PROVIDER: S-EPMC4651451 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment.

Ebisu Keita K Belanger Kathleen K Bell Michelle L ML

Environmental research letters : ERL [Web site] 20140801 8

Several papers reported associations between airborne fine particulate matter (PM2.5) and birth weight, though findings are inconsistent across studies. Conflicting results might be due to (1) different PM2.5 chemical structure across locations, and (2) various exposure assignment methods across studies even among the studies that use ambient monitors to assess exposure. We investigated associations between birth weight and PM2.5 chemical constituents, considerin ...[more]

PMID: 26594233

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Project description:A common practice when analyzing multi-site epidemiological data is to include a term for 'site' to account for unmeasured effects at each location. This practice should be carefully considered when site can have complex relationships with important demographic and exposure variables. We leverage data from three longitudinal North American pregnancy cohorts to demonstrate a novel method to assess study heterogeneity and potential combinability of studies for pooled analyses in order to better understand how to consider site in analyses. Results from linear regression and fixed effects meta-regression models run both prior to and following the proposed combinability analyses were compared. In order to exemplify this approach, we examined associations between prenatal exposure to particulate matter and birth weight. Analyses included mother-child dyads (N=1966) from the Asthma Coalition on Community Environment and Social Stress (ACCESS) Project and the PRogramming of Intergenerational Stress Mechanisms (PRISM) study in the northeastern United States, and the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study in Mexico City. Mothers' daily third trimester exposure to particulate matter?2.5?m in diameter (PM2.5) was estimated using a validated satellite-based spatio-temporally resolved model in all studies. Fenton birth weight for gestational age z-scores were calculated. Linear regression analyses within each cohort separately did not find significant associations between PM2.5 averaged over the third trimester and Fenton z-scores. The initial meta-regression model also did not find significant associations between prenatal PM2.5 and birthweight. Next, propensity scores and log linear models were used to assess higher order interactions and determine if sites were comparable with regard to sociodemographics and other covariates; these analyses demonstrated that PROGRESS and ACCESS were combinable. Adjusted linear regression models including a 2-level site variable according to the pooling indicated by the log linear models (ACCESS and PROGRESS as one level and PRISM as another) revealed that a 5?g/m3 increase in PM2.5 was associated with a 0.075 decrease in Fenton z-score (p<0.0001); linear models including a 3-level site variable did not reveal significant associations. By assessing the combinability of heterogeneous populations prior to combining data using a method that more optimally accounts for underlying cohort differences, we were able to identify significant associations between prenatal PM2.5 exposure and birthweight that were not detected using standard methods.

Project description:BackgroundSeveral epidemiological studies have reported that long-term exposure to fine particulate matter (PM2.5) is associated with higher mortality. Evidence regarding contributions of PM2.5 constituents is inconclusive.ObjectivesWe assembled a data set of 12.5 million Medicare enrollees (? 65 years of age) to determine which PM2.5 constituents are a) associated with mortality controlling for previous-year PM2.5 total mass (main effect); and b) elevated in locations exhibiting stronger associations between previous-year PM2.5 and mortality (effect modification).MethodsFor 518 PM2.5 monitoring locations (eastern United States, 2000-2006), we calculated monthly mortality rates, monthly long-term (previous 1-year average) PM2.5, and 7-year averages (2000-2006) of major PM2.5 constituents [elemental carbon (EC), organic carbon matter (OCM), sulfate (SO42-), silicon (Si), nitrate (NO3-), and sodium (Na)] and community-level variables. We applied a Bayesian hierarchical model to estimate location-specific mortality rates associated with previous-year PM2.5 (model level 1) and identify constituents that contributed to the spatial variability of mortality, and constituents that modified associations between previous-year PM2.5 and mortality (model level 2), controlling for community-level confounders.ResultsOne-standard deviation (SD) increases in 7-year average EC, Si, and NO3- concentrations were associated with 1.3% [95% posterior interval (PI): 0.3, 2.2], 1.4% (95% PI: 0.6, 2.4), and 1.2% (95% PI: 0.4, 2.1) increases in monthly mortality, controlling for previous-year PM2.5. Associations between previous-year PM2.5 and mortality were stronger in combination with 1-SD increases in SO42- and Na.ConclusionsLong-term exposures to PM2.5 and several constituents were associated with mortality in the elderly population of the eastern United States. Moreover, some constituents increased the association between long-term exposure to PM2.5 and mortality. These results provide new evidence that chemical composition can partly explain the differential toxicity of PM2.5.

Dataset Information

The Association between Airborne PM2.5 Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment.

Publications

The Association between Airborne PM<sub>2.5</sub> Chemical Constituents and Birth Weight-Implication of Buffer Exposure Assignment.

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