Abstract
BackgroundThe purpose of this research was to determine the relationship between modeled particulate matter (PM2.5) exposure and birth weight, including the potential modification by maternal risk factors and indicators of socioeconomic status (SES).MethodsBirth records from 2001 to 2006 (N = 231,929) were linked to modeled PM2.5 data from a national land-use regression model along with neighbourhood-level SES and socio-demographic data using 6-digit residential postal codes. Multilevel random coefficient models were used to estimate the effects of PM2.5, SES and other individual and neighbourhood-level covariates on continuous birth weight and test interactions. Gestational age was modeled with a random slope to assess potential neighbourhood-level differences of its effect on birth weight and whether any between-neighbourhood variability can be explained by cross-level interactions.ResultsModels adjusted for individual and neighbourhood-level covariates showed a significant non-linear negative association between PM2.5 and birth weight explaining 8.5 % of the between-neighbourhood differences in mean birth weight. A significant interaction between SES and PM2.5 was observed, revealing a more pronounced negative effect of PM2.5 on birth weight in lower SES neighbourhoods. Further positive and negative modification of the PM2.5 effect was observed with maternal smoking, maternal age, gestational diabetes, and suspected maternal drug or alcohol use. The random intercept variance indicating between-neighbourhood birth weight differences was reduced by 75 % in the final model, while the random slope variance for between-neighbourhood gestational age effects remained virtually unchanged.ConclusionWe provide evidence that neighbourhood-level SES variables and PM2.5 have both independent and interacting associations with birth weight, and together account for 49 % of the between-neighbourhood differences in birth weight. Evidence of effect modification of PM2.5 on birth weight across various maternal and neighbourhood-level factors suggests that certain sub-populations may be more or less vulnerable to relatively low doses PM2.5 exposure.
Highlights
The purpose of this research was to determine the relationship between modeled particulate matter (PM2.5) exposure and birth weight, including the potential modification by maternal risk factors and indicators of socioeconomic status (SES)
We explore the potential for between-neighbourhood variability for the slope of gestational age on birth weight and whether interactions with PM2.5, neighbourhood-level SES indicators, and/or individual-level risk factors are able to explain any neighbourhood-level variability
Data from the BC Perinatal Data Registry were provided by Perinatal Services British Columbia (PSBC) which included information on maternal-infant health status and outcomes, reproductive history, maternal risk factors and attributes, and residential postal codes
Summary
The purpose of this research was to determine the relationship between modeled particulate matter (PM2.5) exposure and birth weight, including the potential modification by maternal risk factors and indicators of socioeconomic status (SES). Excess or uncontrolled oxidative stress and inflammation early in pregnancy may disrupt placental cell growth and differentiation, potentially leading to deficient deep placentation and morphological adaptations associated with several adverse pregnancy outcomes including fetal growth restriction [10] These mechanisms by which PM2.5 may act to adversely impact the reproductive system are not fully understood; evidence supports the potential for a shared mode of developmental toxicity with several other known risk factors [5, 11]. This includes factors that promote or are associated with oxidative stress and inflammation such as smoking [12], drug use [13], advanced maternal age [14] gestational diabetes [15], and low socioeconomic status (SES) in general [16]. This impact of the social environment on health behaviours and outcomes creates hierarchical structures within which individuals are nested in neighbourhoods and communities with their own set of attributes that can promote or antagonize health and healthy behaviours [19, 20]
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