Rahmalia A.,French Institute of Health and Medical Research |
Giorgis-Allemand L.,French Institute of Health and Medical Research |
Giorgis-Allemand L.,Institut Universitaire de France |
Lepeule J.,French Institute of Health and Medical Research |
And 9 more authors.
Environment International | Year: 2012
Background: Epidemiologic studies suggest an association between air pollution exposure and foetal growth. The possible underlying biological mechanisms have little been studied in humans, but animal studies suggest an impact of atmospheric pollutants on placental function. Objectives: Our aim was to investigate the association between exposure to atmospheric pollutants' levels during pregnancy and placental weight, birth weight and the placental to foetal weights ratio (PFR). For comparison purposes, the effects of active smoking on the same measures at birth have also been estimated. Methods: The study relies on women from Eden mother-child cohort recruited in the middle-sized cities of Poitiers and Nancy (France). Nitrogen dioxide (NO2) and particulate matter with diameter <10μm (PM10) home address levels during pregnancy were assessed using ADMS-Urban dispersion model. We characterized associations of NO2, PM10 levels and active smoking with placental, birth weights and PFR by distinct linear regression models. Results: Air pollution levels were higher and had greater variability in Nancy (5th-95th centiles, 19.9-27.9μg/m3 for PM10) than in Poitiers (5th-95th centiles, 14.3-17.8μg/m3). Associations differed by study area: in Nancy (355 births), air pollution levels were associated with decreased placental weight and PFR, while in Poitiers (446 births), opposite or null associations were observed. Cigarette smoking was not associated with placental weight while it was associated with a decrease in birth weight and an increase in PFR. Conclusion: Results regarding air pollution estimated effects were not similar in both study areas and should therefore be taken with caution. The placental weight decrease observed with air pollutants in the more polluted area of Nancy is consistent with a recent epidemiological study. In this area, maternal active smoking and PM10 levels tended to have opposite effects on the PFR, suggesting different mechanisms of action of both pollutants on foetal growth. © 2012 Elsevier Ltd.
Signoret J.,Air Lorraine |
Schmitt J.-P.,Air Lorraine
Pollution Atmospherique | Year: 2011
Simple, effective and inexpensive, air pollution biomonitoring appears as a complementary approach of physical and chemical actions. In full development, standardization methods of biomonitoring by AFNOR French and European CEN strengthens this approach and provides a framework for more attractive to potential users that are the French associations approved for monitoring of the air quality (AASQA) which are grouped within the ATMO France Federation. Two surveys conducted in 2008 and 2011 with the assistance of the air quality monitoring networks, show that, despite the importance of resources dedicated by some of these associations for the implementation of the biomonitoring methods, the generalization of this approach is more that tough differences of integration in the programmes and regulatory plans, awareness and access to the capabilities. This article highlights the potential of biomonitoring in the AASQA for informing policy in the field of air quality monitoring.
Pedersen M.,Center for Research in Environmental Epidemiology |
Pedersen M.,IMIM Hospital del Mar Research Institute |
Pedersen M.,CIBER ISCIII |
Pedersen M.,French Institute of Health and Medical Research |
And 25 more authors.
Environment International | Year: 2013
Background: Spatially-resolved air pollution models can be developed in large areas. The resulting increased exposure contrasts and population size offer opportunities to better characterize the effect of atmospheric pollutants on respiratory health. However the heterogeneity of these areas may also enhance the potential for confounding. We aimed to discuss some analytical approaches to handle this trade-off. Methods: We modeled NO2 and PM10 concentrations at the home addresses of 1082 pregnant mothers from EDEN cohort living in and around urban areas, using ADMS dispersion model. Simulations were performed to identify the best strategy to limit confounding by unmeasured factors varying with area type. We examined the relation between modeled concentrations and respiratory health in infants using regression models with and without adjustment or interaction terms with area type. Results: Simulations indicated that adjustment for area limited the bias due to unmeasured confounders varying with area at the costs of a slight decrease in statistical power. In our cohort, rural and urban areas differed for air pollution levels and for many factors associated with respiratory health and exposure. Area tended to modify effect measures of air pollution on respiratory health. Conclusions: Increasing the size of the study area also increases the potential for residual confounding. Our simulations suggest that adjusting for type of area is a good option to limit residual confounding due to area-associated factors without restricting the area size. Other statistical approaches developed in the field of spatial epidemiology are an alternative to control for poorly-measured spatially-varying confounders. © 2013 Elsevier Ltd.
Yann S.,French Institute of Health and Medical Research |
Yann S.,Joseph Fourier University |
Galineau J.,Air Lorraine |
Hulin A.,ATMO Poitou Charentes |
And 13 more authors.
Environment International | Year: 2014
Background: Spatially resolved exposure models are increasingly used in epidemiology. We previously reported that, although exhibiting a moderate correlation, pregnancy nitrogen dioxide (NO2) levels estimated by the nearest air quality monitoring station (AQMS) model and a geostatistical model, showed similar associations with infant birth weight. Objectives: We extended this study by comparing a total of four exposure models, including two highly spatially resolved models: a land-use regression (LUR) model and a dispersion model. Comparisons were made in terms of predicted NO2 and particle (aerodynamic diameter<10μm, PM10) exposure and adjusted association with birth weight. Methods: The four exposure models were implemented in two French metropolitan areas where 1026 pregnant women were followed as part of the EDEN mother-child cohort. Results: Correlations between model predictions were high (≥0.70), except for NO2 between the AQMS and both the LUR (r=0.54) and dispersion models (r=0.63). Spatial variations as estimated by the AQMS model were greater for NO2 (95%) than for PM10 (22%). The direction of effect estimates of NO2 on birth weight varied according to the exposure model, while PM10 effect estimates were more consistent across exposure models. Conclusions: For PM10, highly spatially resolved exposure model agreed with the poor spatial resolution AQMS model in terms of estimated pollutant levels and health effects. For more spatially heterogeneous pollutants like NO2, although predicted levels from spatially resolved models (all but AQMS) agreed with each other, our results suggest that some may disagree with each other as well as with the AQMS regarding the direction of the estimated health effects. © 2014 Elsevier Ltd.