Effects of air pollution on clinical pregnancy rates after in vitro fertilisation (IVF): a retrospective cohort study.

OBJECTIVE: To evaluate the effect of air pollution, from oocyte retrieval to embryo transfer, on the results of in vitro fertilisation (IVF) in terms of clinical pregnancy rates, at two fertility centres, from 2013 to 2019. DESIGN: Exploratory retrospective cohort study. SETTING: This retrospective cohort study was performed in the Reproductive Biology Department of Bordeaux University Hospital localised in Bordeaux, France and the Jean Villar Fertility Center localised in Bruges, France. PARTICIPANTS: This study included 10 763 IVF attempts occurring between January 2013 and December 2019, 2194 of which resulted in a clinical pregnancy. PRIMARY AND SECONDARY OUTCOME MEASURES: The outcome of the IVF attempt was recorded as the presence or absence of a clinical pregnancy; exposure to air pollution was assessed by calculating the cumulative exposure of suspended particulate matter, fine particulate matter, black carbon, nitrogen dioxide and ozone (O3), over the period from oocyte retrieval to embryo transfer, together with secondary exposure due to the presence of the biomass boiler room, which was installed in 2016, close to the Bordeaux University Hospital laboratory. The association between air pollution and IVF outcome was evaluated by a random-effects logistic regression analysis. RESULTS: We found negative associations between cumulative O3 exposure and clinical pregnancy rate (OR=0.92, 95% CI = (0.86 to 0.98)), and between biomass boiler room exposure and clinical pregnancy rate (OR=0.75, 95% CI = (0.61 to 0.91)), after adjustment for potential confounders. CONCLUSION: Air pollution could have a negative effect on assisted reproductive technology results and therefore precautions should be taken to minimise the impact of outdoor air on embryo culture.

Maternal Ambient Exposure to Atmospheric Pollutants during Pregnancy and Offspring Term Birth Weight in the Nationwide ELFE Cohort.

BACKGROUND: Studies have reported associations between maternal exposure to atmospheric pollution and lower birth weight. However, the evidence is not consistent and uncertainties remain. We used advanced statistical approaches to robustly estimate the association of atmospheric pollutant exposure during specific pregnancy time windows with term birth weight (TBW) in a nationwide study. METHODS: Among 13,334 women from the French Longitudinal Study of Children (ELFE) cohort, exposures to PM2.5, PM10 (particles < 2.5 µm and <10 µm) and NO2 (nitrogen dioxide) were estimated using a fine spatio-temporal exposure model. We used inverse probability scores and doubly robust methods in generalized additive models accounting for spatial autocorrelation to study the association of such exposures with TBW. RESULTS: First trimester exposures were associated with an increased TBW. Second trimester exposures were associated with a decreased TBW by 17.1 g (95% CI, -26.8, -7.3) and by 18.0 g (-26.6, -9.4) for each 5 µg/m3 increase in PM2.5 and PM10, respectively, and by 15.9 g (-27.6, -4.2) for each 10 µg/m3 increase in NO2. Third trimester exposures (truncated at 37 gestational weeks) were associated with a decreased TBW by 48.1 g (-58.1, -38.0) for PM2.5, 38.1 g (-46.7, -29.6) for PM10 and 14.7 g (-25.3, -4.0) for NO2. Effects of pollutants on TBW were larger in rural areas. CONCLUSIONS: Our results support an adverse effect of air pollutant exposure on TBW. We highlighted a larger effect of air pollutants on TBW among women living in rural areas compared to women living in urban areas.

Monitoring of pesticides in ambient air: Prioritization of substances.

Despite the richness of data collected on pesticide concentrations in ambient air in France, knowledge on this topic remains partial and heterogeneous in the absence of specific regulations. The population exposure remains thus difficult to estimate; therefore it was necessary to define modalities for implementing national monitoring of pesticides in ambient air in metropolitan France and in the overseas territories. The objective of this work was to identify which active substances (a.s.) have to be monitored in priority. As part of a collective expertise, a group of multidisciplinary experts has developed a method to rank active substances authorised as plant protection products, biocides and antiparasitic agents, which were available on the French market in 2015. A 3-steps approach has been developed. The first step consisted of a theoretical approach based on a hierarchy of substances according to four criteria: (a) national uses, (b) emission potential to the air, (c) persistence in the air, and (d) chronic toxicity. The three first criteria give information on their potential to be present in the atmosphere, and the fourth criterion allows to consider their potential of hazard. The second step was an observational approach based on existing database on pesticide air measurements in France. In the third step, both approaches were combined using decision trees to select priority pesticides. Among the 1316 a.s. first identified from the EU Pesticides database, 90 were selected, among which 43 required metrological and/or analytical development. The experts recommended confirming the relevance of performing a longer term monitoring of these a. s. after a one-year exploratory campaign. The proposed method is reproduceable, transparent, easy to update (e.g. in the light of a change in product authorization), and can be adapted to other agricultural and geographical conditions, and objectives (e.g. monitoring of the ecotoxicological effects of pesticides).

Pregnancy exposure to atmospheric pollution and meteorological conditions and placental DNA methylation.

BACKGROUND: Air pollution exposure represents a major health threat to the developing foetus. DNA methylation is one of the most well-known molecular determinants of the epigenetic status of cells. Blood DNA methylation has been proven sensitive to air pollutants, but the molecular impact of air pollution on new-borns has so far received little attention. OBJECTIVES: We investigated whether nitrogen dioxide (NO2), particulate matter (PM10), temperature and humidity during pregnancy are associated with differences in placental DNA methylation levels. METHODS: Whole-genome DNA-methylation was measured using the Illumina's Infinium HumanMethylation450 BeadChip in the placenta of 668 newborns from the EDEN cohort. We designed an original strategy using a priori biological information to focus on candidate genes with a specific expression pattern in placenta (active or silent) combined with an agnostic epigenome-wide association study (EWAS). We used robust linear regression to identify CpGs and differentially methylated regions (DMR) associated with each exposure during short- and long-term time-windows. RESULTS: The candidate genes approach identified nine CpGs mapping to 9 genes associated with prenatal NO2 and PM10 exposure [false discovery rate (FDR) p < 0.05]. Among these, the methylation level of 2 CpGs located in ADORA2B remained significantly associated with NO2 exposure during the 2nd trimester and whole pregnancy in the EWAS (FDR p < 0.05). EWAS further revealed associations between the environmental exposures under study and variations of DNA methylation of 4 other CpGs. We further identified 27 DMRs significantly (FDR p < 0.05) associated with air pollutants exposure and 13 DMRs with meteorological conditions. CONCLUSIONS: The methylation of ADORA2B, a gene whose expression was previously associated with hypoxia and pre-eclampsia, was consistently found here sensitive to atmospheric pollutants. In addition, air pollutants were associated to DMRs pointing towards genes previously implicated in preeclampsia, hypertensive and metabolic disorders. These findings demonstrate that air pollutants exposure at levels commonly experienced in the European population are associated with placental gene methylation and provide some mechanistic insight into some of the reported effects of air pollutants on preeclampsia.

Health effects of ambient air pollution: do different methods for estimating exposure lead to different results?

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<10 µm, 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.

Does consideration of larger study areas yield more accurate estimates of air pollution health effects? An illustration of the bias-variance trade-off in air pollution epidemiology.

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.

Pregnancy exposure to atmospheric pollutants and placental weight: an approach relying on a dispersion model.

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 (NO(2)) and particulate matter with diameter <10 µm (PM10) home address levels during pregnancy were assessed using ADMS-Urban dispersion model. We characterized associations of NO(2), 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, 19.9-27.9 µg/m(3) for PM10) than in Poitiers (5th-95th centiles, 14.3-17.8 µg/m(3)). 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.

Maternal exposure to nitrogen dioxide during pregnancy and offspring birth weight: comparison of two exposure models.

BACKGROUND: Studies of the effects of air pollutants on birth weight often assess exposure with networks of permanent air quality monitoring stations (AQMSs), which have a poor spatial resolution. OBJECTIVE: We aimed to compare the exposure model based on the nearest AQMS and a temporally adjusted geostatistical (TAG) model with a finer spatial resolution, for use in pregnancy studies. METHODS: The AQMS and TAG exposure models were implemented in two areas surrounding medium-size cities in which 776 pregnant women were followed as part of the EDEN mother-child cohort. The exposure models were compared in terms of estimated nitrogen dioxide (NO2) levels and of their association with birth weight. RESULTS: The correlations between the two estimates of exposure during the first trimester of pregnancy were r = 0.67, 0.70, and 0.83 for women living within 5, 2, and 1 km of an AQMS, respectively. Exposure patterns displayed greater spatial than temporal variations. Exposure during the first trimester of pregnancy was most strongly associated with birth weight for women living < 2 km away from an AQMS: a 10-µg/m3 increase in NO2 exposure was associated with an adjusted difference in birth weight of -37 g [95% confidence interval (CI), -75 to 1 g] for the nearest-AQMS model and of -51 g (95% CI, -128 to 26 g) for the TAG model. The association was less strong (higher p-value) for women living within 5 or 1 km of an AQMS. CONCLUSIONS: The two exposure models tended to give consistent results in terms of association with birth weight, despite the moderate concordance between exposure estimates.