Air pollution and human fertility rates Nieuwenhuijsen, Mark J.; Basagaña, Xavier; Dadvand, Payam ...
Environment international,
09/2014, Volume:
70
Journal Article
Peer reviewed
Some reports have suggested effects of air pollution on semen quality and success rates of in vitro fertilization (IVF) in humans and lower fertility rates in mice. However, no studies have evaluated ...the impact of air pollution on human fertility rates.
We assessed the association between traffic related air pollution and fertility rates in humans in Barcelona, Spain (2011–2012). We hypothesized that higher air pollution levels would be associated with lower fertility rates.
We calculated the general fertility rate which is the number of live births per 1000 women between the ages of 15 and 44years per census tract. We used land use regression (LUR) modeling to estimate the air pollution concentrations (particulate matter, NO2/NOx) per census tract. We used Besag–York–Mollié models to quantify the relationship between air pollution and fertility rates with adjustment for a number of potential confounders such as maternal age and area level socio-economic status.
We found a statistically significant reduction of fertility rates with an increase in traffic related air pollution levels, particularly for the coarse fraction of particulate matter (IRR=0.87 95% CI 0.82, 0.94 per IQR).
This is the first study in humans to show an association between reduced fertility rates and higher traffic related air pollution levels.
•A few studies in mice have shown that air pollution may lower fertility rates, but there were no studies in humans•This study showed a reduction in human fertility rates with higher air pollution levels, specifically for the PMcoarse fraction•Since this is the first human study, further studies are needed to confirm or refute the results.
This study is conducted to characterize the intra-urban distribution of NOx and NO2; develop land use regression (LUR) models to assess outdoor NOx and NO2 concentrations, using the ESCAPE modeling ...approach with locally specific land use data; and compare NOx and NO2 exposures for children in the Taipei Metropolis by the LUR models, the nearest monitoring station, and kriging methods based on data collected at the measurement sites. NOx and NO2 were measured for 2weeks during 3 seasons at 40 sampling sites by Ogawa passive badges to represent their concentrations at urban backgrounds and streets from October 2009 to September 2010. Land use data and traffic-related information in different buffer zones were combined with measured concentrations to derive LUR models using supervised forward stepwise multiple regressions. The annual average concentrations of NOx and NO2 in Taipei were 72.4±22.5 and 48.9±12.2μg/m3, respectively, which were at the high end of all 36 European areas in the ESCAPE project. Spatial contrasts in Taipei were lower than those of the European areas in the ESCAPE project. The NOx LUR model included 6 land use variables, which were lengths of major roads within 25m, 25–50m, and 50–500m, urban green areas within 300m and 300–5000m, and semi-natural and forested areas within 500m, with R2=0.81. The NO2 LUR model included 4 land use variables, which were lengths of major roads within 25m, urban green areas within 100m, semi-natural and forested areas within 500m, and low-density residential area within 500m, with R2=0.74. The LUR models gave a wider variation in estimating NOx and NO2 exposures than either the ordinary kriging method or the nearest measurement site did for the children of Taiwan Birth Cohort Study (TBCS) in Taipei.
•NOx and NO2 pollution in Taipei has high concentrations but low spatial contrast.•The ESCAPE-based LUR models can estimate residents' NOx and NO2 exposure in Taipei.•Traffic emissions are a major contribution to NOx and NO2 exposures in Taipei.
Ambient air pollution has been associated with restricted fetal growth, which is linked with adverse respiratory health in childhood. We assessed the effect of maternal exposure to low concentrations ...of ambient air pollution on birthweight.
We pooled data from 14 population-based mother-child cohort studies in 12 European countries. Overall, the study population included 74 178 women who had singleton deliveries between Feb 11, 1994, and June 2, 2011, and for whom information about infant birthweight, gestational age, and sex was available. The primary outcome of interest was low birthweight at term (weight <2500 g at birth after 37 weeks of gestation). Mean concentrations of particulate matter with an aerodynamic diameter of less than 2·5 μm (PM2·5), less than 10 μm (PM10), and between 2·5 μm and 10 μm during pregnancy were estimated at maternal home addresses with temporally adjusted land-use regression models, as was PM2·5 absorbance and concentrations of nitrogen dioxide (NO2) and nitrogen oxides. We also investigated traffic density on the nearest road and total traffic load. We calculated pooled effect estimates with random-effects models.
A 5 μg/m(3) increase in concentration of PM2·5 during pregnancy was associated with an increased risk of low birthweight at term (adjusted odds ratio OR 1·18, 95% CI 1·06-1·33). An increased risk was also recorded for pregnancy concentrations lower than the present European Union annual PM2·5 limit of 25 μg/m(3) (OR for 5 μg/m(3) increase in participants exposed to concentrations of less than 20 μg/m(3) 1·41, 95% CI 1·20-1·65). PM10 (OR for 10 μg/m(3) increase 1·16, 95% CI 1·00-1·35), NO2 (OR for 10 μg/m(3) increase 1·09, 1·00-1·19), and traffic density on nearest street (OR for increase of 5000 vehicles per day 1·06, 1·01-1·11) were also associated with increased risk of low birthweight at term. The population attributable risk estimated for a reduction in PM2·5 concentration to 10 μg/m(3) during pregnancy corresponded to a decrease of 22% (95% CI 8-33%) in cases of low birthweight at term.
Exposure to ambient air pollutants and traffic during pregnancy is associated with restricted fetal growth. A substantial proportion of cases of low birthweight at term could be prevented in Europe if urban air pollution was reduced.
The European Union.
Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR ...model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project.
Nitrogen dioxide (NO2) and nitrogen oxides (NOx) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modelling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance.
There was substantial contrast in annual average NO2 and NOx concentrations within the study areas. The model explained variances (R2) of the LUR models ranged from 55% to 92% (median 82%) for NO2 and from 49% to 91% (median 78%) for NOx. For most areas the cross-validation R2 was less than 10% lower than the model R2. Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower R2 compared to models in the same areas in which these variables were offered.
Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO2 and NOx concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies.
► LUR models were developed in 36 study areas in Europe using a standardized approach. ► NO2 models explained a large fraction of concentration variability (median R2 82%). ► Local traffic intensity data were important predictors for LUR model development.
Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort ...studies. Within the ESCAPE project, concentrations of PM2.5, PM2.5 absorbance, PM10, and PMcoarse were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R 2) was 71% for PM2.5 (range across study areas 35–94%). Model R 2 was higher for PM2.5 absorbance (median 89%, range 56–97%) and lower for PMcoarse (median 68%, range 32– 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R 2 was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R 2 results were on average 8–11% lower than model R 2. Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.
Background: Maternal residential proximity to roads has been associated with adverse pregnancy outcomes. However, there is no study investigating mediators or buffering effects of road-adjacent trees ...on this association. We investigated the association between mothers' residential proximity to major roads and term low birth weight (LBW), while exploring possible mediating roles of air pollution (PM2.5, PM2.5–10, PM10, PM2.5 absorbance, nitrogen dioxide, and nitrogen oxides), heat, and noise and buffering effect of road-adjacent trees on this association. Methods: This cohort study was based on 6438 singleton term births in Barcelona, Spain (2001–2005). Road proximity was measured as both continuous distance to and living within 200 m from a major road. We assessed individual exposures to air pollution, noise, and heat using, respectively, temporally adjusted land-use regression models, annual averages of 24-hour noise levels across 50 m and 250 m, and average of satellite-derived land-surface temperature in a 50-m buffer around each residential address. We used vegetation continuous fields to abstract tree coverage in a 200-m buffer around major roads. Results: Living within 200 m of major roads was associated with a 46% increase in term LBW risk; an interquartile range increase in heat exposure with an 18% increase; and third-trimester exposure to PM2.5, PM2.5–10, and PM10 with 24%, 25%, and 26% increases, respectively. Air pollution and heat exposures together explained about one-third of the association between residential proximity to major roads and term LBW. Our observations on the buffering of this association by road-adjacent trees were not consistent between our 2 measures of proximity to major roads. Conclusion: An increased risk of term LBW associated with proximity to major roads was partly mediated by air pollution and heat exposures.
The origin(s) of systemic inflammation in patients with chronic obstructive pulmonary disease (COPD) is unclear. We investigated the impact of exposure to ambient air pollution on systemic biomarkers ...of inflammation (C-reactive protein (CRP), tumour necrosis factor-α, interleukin (IL)-6, IL-8 and fibrinogen) and tissue repair (hepatocyte growth factor (HGF)) in 242 clinically stable COPD patients (mean age 67.8 years and forced expiratory volume in 1 s 71.3% predicted) in Barcelona, Spain, in 2004-2006. A spatiotemporal exposure assessment framework was applied to predict ambient nitrogen dioxide (NO2) and levels of particles with a 50% cut-off aerodynamic diameter of 2.5 μm (PM2.5) at each participant's home address during 10 periods of 24 h (lags 1-10) and 1 year prior to the blood sampling date. We used linear regression models to estimate associations between biomarkers and exposure levels. An interquartile range (IQR) increase in NO2 exposure in lag 5 was associated with 51%, 10% and 9% increases in CRP, fibrinogen and HGF levels respectively. We also observed 12% and 8% increases in IL-8 associated with an IQR increase in NO2 exposure in lag 3 and over the year before sampling, respectively. These increases were larger in former smokers. The results for PM2.5 were not conclusive. These results show that exposure to ambient NO2 increases systemic inflammation in COPD patients, especially in former smokers.
Childhood blood pressure is an important predictor of hypertension and cardiovascular disease in adulthood. Evidence for an association between ambient particulate matter (PM) exposure and blood ...pressure is increasing, but little is known about the relevance of different PM constituents.
We investigated the association between particulate matter composition and blood pressure at age 12years.
Annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc in particles with diameters of less than 2.5μm (PM2.5) and 10μm (PM10) were estimated by land-use regression modeling for the home addresses of the participants of the prospective PIAMA birth cohort study. Associations between element concentrations and blood pressure measurements performed at age 12years were investigated by linear regression with and without adjustment for confounders.
After adjustment for potential confounders we found statistically significant positive associations of diastolic blood pressure with iron, silicon, and potassium in PM10 in children who lived at the same address since birth mean difference (95% confidence interval) 0.67 (0.02;1.31) mmHg, 0.85 (0.18;1.52) mmHg, and 0.75 (0.09;1.41) mmHg, respectively, per interquartile range increase in exposure. Also, we found marginally significant (p<0.1) positive associations between iron and silicon in PM2.5 and diastolic blood pressure. Part of the observed effects was found to be attributable to NO2, a marker of exhaust traffic emissions.
Exposure to particulate matter constituents, in particular iron may increase blood pressure in children. The possible association with iron may indicate the health relevance of non-exhaust emissions of traffic.
•Childhood blood pressure is a predictor of adulthood cardiovascular disease•The role of ambient particulate matter constituents for blood pressure is unknown.•In particular iron and silicon in PM was associated with diastolic blood pressure.•The association with iron indicates the relevance of non-exhaust traffic emissions.
The International Agency for Research on Cancer (IARC) recently declared air pollution carcinogenic to humans. However, no study of air pollution and lung cancer to date has incorporated adjustment ...for exposure measurement error, and few have examined specific histological subtypes.
Our aim was to assess the association of air pollution and incident lung cancer in the Netherlands Cohort Study on Diet and Cancer and the impact of measurement error on these associations.
The cohort was followed from 1986 through 2003, and 3,355 incident cases were identified. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals, for long-term exposures to nitrogen dioxide (NO2), black smoke (BS), PM2.5 (particulate matter with diameter ≤ 2.5 μm), and measures of roadway proximity and traffic volume, adjusted for potential confounders. Information from a previous validation study was used to correct the effect estimates for measurement error.
We observed elevated risks of incident lung cancer with exposure to BS hazard ratio (HR) = 1.16; 95% CI: 1.02, 1.32, per 10 μg/m3, NO2 (HR = 1.29; 95% CI: 1.08, 1.54, per 30 μg/m3), PM2.5 (HR = 1.17; 95% CI: 0.93, 1.47, per 10 μg/m3), and with measures of traffic at the baseline address. The exposures were positively associated with all lung cancer subtypes. After adjustment for measurement error, the HRs increased and the 95% CIs widened HR = 1.19 (95% CI: 1.02, 1.39) for BS and HR = 1.37 (95% CI: 0.86, 2.17) for PM2.5.
These findings add support to a growing body of literature on the effects of air pollution on lung cancer. In addition, they highlight variation in measurement error by pollutant and support the implementation of measurement error corrections when possible.
Hart JE, Spiegelman D, Beelen R, Hoek G, Brunekreef B, Schouten LJ, van den Brandt P. 2015. Long-term ambient residential traffic-related exposures and measurement error-adjusted risk of incident lung cancer in the Netherlands Cohort Study on Diet and Cancer. Environ Health Perspect 123:860-866; http://dx.doi.org/10.1289/ehp.1408762.
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