Air pollution exposure estimation using dispersion modelling and continuous monitoring data in a prospective birth cohort study in The Netherlands

Prenatal Exposure to Nitrogen Oxides and its Association with Birth Weight in a Cohort of Mexican Newborns from Morelos, Mexico

Background

The Child-Mother binomial is potentially susceptible to the toxic effects of pollutants because some chemicals interfere with placental transfer of nutrients, thus affecting fetal development, and create an increased the risk of low birth weight, prematurity and intrauterine growth restriction.

Objective

To evaluate the impact of prenatal exposure to nitrogen oxides (NO_x) on birth weight in a cohort of Mexican newborns.

Methodology

We included 745 mother-child pair participants of the POSGRAD cohort study. Information on socio-demographic characteristics, obstetric history, health history and environmental exposure during pregnancy were readily available and the newborns’ anthropometric measurements were obtained at delivery. Prenatal NO_x exposure assessment was evaluated using a Land-Use Regression predictive models considering local monitoring from 60 sites on the State of Morelos. The association between prenatal exposure to NO_x and birth weight was estimated using a multivariate linear regression models.

Results

The average birth weight was 3217 ± 439 g and the mean of NO_x concentration was 21 ppb (Interquartile range, IQR = 6.95 ppb). After adjusting for maternal age and other confounders, a significant birthweight reduction was observed for each IQR of NO_x increase (ß = –39.61 g, 95% CI: –77.00; –2.21; p = 0.04).

Conclusions

Our results provides evidence that prenatal NO_x exposure has a negative effect on birth weight, which may influence the growth and future development of the newborn.

Local- and regional-scale air pollution modelling (PM10) and exposure assessment for pregnancy trimesters, infancy, and childhood to age 15 years: Avon Longitudinal Study of Parents And Children (ALSPAC)

We established air pollution modelling to study particle (PM₁₀) exposures during pregnancy and infancy (1990-1993) through childhood and adolescence up to age ~15 years (1991-2008) for the Avon Longitudinal Study of Parents And Children (ALSPAC) birth cohort. For pregnancy trimesters and infancy (birth to 6 months; 7 to 12 months) we used local (ADMS-Urban) and regional/long-range (NAME-III) air pollution models, with a model constant for local, non-anthropogenic sources. For longer exposure periods (annually and the average of birth to age ~8 and to age ~15 years to coincide with relevant follow-up clinics) we assessed spatial contrasts in local sources of PM₁₀ with a yearly-varying concentration for all background sources. We modelled PM₁₀ (μg/m³) for 36,986 address locations over 19 years and then accounted for changes in address in calculating exposures for different periods: trimesters/infancy (n = 11,929); each year of life to age ~15 (n = 10,383). Intra-subject exposure contrasts were largest between pregnancy trimesters (5^th to 95^th centile: 24.4-37.3 μg/m³) and mostly related to temporal variability in regional/long-range PM₁₀. PM₁₀ exposures fell on average by 11.6 μg/m³ from first year of life (mean concentration = 31.2 μg/m³) to age ~15 (mean = 19.6 μg/m³), and 5.4 μg/m³ between follow-up clinics (age ~8 to age ~15). Spatial contrasts in 8-year average PM₁₀ exposures (5^th to 95^th centile) were relatively low: 25.4-30.0 μg/m³ to age ~8 years and 20.7-23.9 μg/m³ from age ~8 to age ~15 years. The contribution of local sources to total PM₁₀ was 18.5%-19.5% during pregnancy and infancy, and 14.4%-17.0% for periods leading up to follow-up clinics. Main roads within the study area contributed on average ~3.0% to total PM₁₀ exposures in all periods; 9.5% of address locations were within 50 m of a main road. Exposure estimates will be used in a number of planned epidemiological studies.

Air pollution modelling for birth cohorts: a time-space regression model

BACKGROUND

To investigate air pollution effects during pregnancy or in the first weeks of life, models are needed that capture both the spatial and temporal variability of air pollution exposures.

METHODS

We developed a time-space exposure model for ambient NO2 concentrations in Bern, Switzerland. We used NO2 data from passive monitoring conducted between 1998 and 2009: 101 rural sites (24,499 biweekly measurements) and 45 urban sites (4350 monthly measurements). We evaluated spatial predictors (land use; roads; traffic; population; annual NO2 from a dispersion model) and temporal predictors (meteorological conditions; NO2 from continuous monitoring station). Separate rural and urban models were developed by multivariable regression techniques. We performed ten-fold internal cross-validation, and an external validation using 57 NO2 passive measurements obtained at study participant's homes.

RESULTS

Traffic related explanatory variables and fixed site NO2 measurements were the most relevant predictors in both models. The coefficient of determination (R(2)) for the log transformed models were 0.63 (rural) and 0.54 (urban); cross-validation R(2)s were unchanged indicating robust coefficient estimates. External validation showed R(2)s of 0.54 (rural) and 0.67 (urban).

CONCLUSIONS

This approach is suitable for air pollution exposure prediction in epidemiologic research with time-vulnerable health effects such as those occurring during pregnancy or in the first weeks of life.

The statistical evaluation and comparison of ADMS-Urban model for the prediction of nitrogen dioxide with air quality monitoring network

In many countries, road traffic is one of the main sources of air pollution associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered to be a measure of traffic-related air pollution, with concentrations tending to be higher near highways, along busy roads, and in the city centers, and the exceedances are mainly observed at measurement stations located close to traffic. In order to assess the air quality in the city and the air pollution impact on public health, air quality models are used. However, firstly, before the model can be used for these purposes, it is important to evaluate the accuracy of the dispersion modelling as one of the most widely used method. The monitoring and dispersion modelling are two components of air quality monitoring system (AQMS), in which statistical comparison was made in this research. The evaluation of the Atmospheric Dispersion Modelling System (ADMS-Urban) was made by comparing monthly modelled NO2 concentrations with the data of continuous air quality monitoring stations in Kaunas city. The statistical measures of model performance were calculated for annual and monthly concentrations of NO2 for each monitoring station site. The spatial analysis was made using geographic information systems (GIS). The calculation of statistical parameters indicated a good ADMS-Urban model performance for the prediction of NO2. The results of this study showed that the agreement of modelled values and observations was better for traffic monitoring stations compared to the background and residential stations.

Correlation of noise levels and particulate matter concentrations near two major freeways in Los Angeles, California

Near-freeway environments are important from public health and environmental justice perspectives. This study investigated the spatial profile of and correlations between noise levels and particulate matter concentrations near two major freeways in Los Angeles, CA. Five minutes averages of A-weighted equivalent continuous sound level (LeqA), ultrafine particle (UFP) number concentrations, and fine particle (PM2.5) mass concentrations were measured concurrently at increasing distances from the freeways on four streets with or without sound wall. Under upwind conditions, UFP showed relatively low concentrations and no obvious gradient, while LeqA showed decay with increasing distance as it did under downwind conditions. Moderate correlations between LeqA and UFP were observed under downwind conditions on all four streets. The presence of a sound wall changed the linear relationship between LeqA and UFP. These data may be used to study the independent and synergistic health impacts of noise and air pollutants near roadways.

Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children

In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.

Air pollution exposure and markers of placental growth and function: the generation R study

BACKGROUND

Air pollution exposure during pregnancy might affect placental growth and function, perhaps leading to pregnancy complications.

OBJECTIVE

We prospectively evaluated the associations of maternal air pollution exposure with markers of placental growth and function among 7,801 pregnant women in the Netherlands.

METHODS

We estimated levels of particulate matter ≤ 10 µm in aerodynamic diameter (PM10) and nitrogen dioxide (NO2) at the home address for different periods during pregnancy using dispersion modeling techniques. Pro- and anti-angiogenic factors [placental growth factor (PlGF) and soluble fms-like tyrosine kinase 1 (sFlt-1), respectively] were measured in first- and second-trimester maternal blood and in fetal cord blood samples at delivery. Pulsatility index of the uterine and umbilical arteries was measured by Doppler ultrasound in second and third trimester, and notching was assessed in third trimester. Placenta weight and birth weight were obtained from medical records.

RESULTS

Higher PM10 and NO2 exposure levels were associated with lower second-trimester maternal sFlt-1 and PlGF levels. PM10 and NO2 exposures averaged over total pregnancy were associated with higher sFlt-1 and lower PlGF levels in fetal cord blood, consistent with an anti-angiogenic state. PM10 and NO2 exposures were not consistently associated with second- or third-trimester placental resistance indices. NO2 exposure was associated with third-trimester notching (odds ratio 1.33; 95% CI: 0.99, 1.78 per 10-µg/m3 increase in the prior 2 months). PM10 and NO2 exposures were associated with lower placenta weight (-11.8 g; 95% CI: -20.9, -2.7, and -10.7 g; 95% CI: -19.0, -2.4, respectively, per 10-µg/m3 increase in the prior 2 months), but not with placenta to birth weight ratio.

CONCLUSIONS

Our results suggest that maternal air pollution exposure may influence markers of placental growth and function. Future studies are needed to confirm these findings and explore the maternal and fetal consequences.