Few studies have investigated traffic-related air pollution as a risk factor for respiratory infections during early childhood.
We aimed to investigate the association between air pollution and ...pneumonia, croup, and otitis media in 10 European birth cohorts--BAMSE (Sweden), GASPII (Italy), GINIplus and LISAplus (Germany), MAAS (United Kingdom), PIAMA (the Netherlands), and four INMA cohorts (Spain)--and to derive combined effect estimates using meta-analysis.
Parent report of physician-diagnosed pneumonia, otitis media, and croup during early childhood were assessed in relation to annual average pollutant levels nitrogen dioxide (NO2), nitrogen oxide (NOx), particulate matter≤2.5 μm (PM2.5), PM2.5 absorbance, PM10, PM2.5-10 (coarse PM), which were estimated using land use regression models and assigned to children based on their residential address at birth. Identical protocols were used to develop regression models for each study area as part of the ESCAPE project. Logistic regression was used to calculate adjusted effect estimates for each study, and random-effects meta-analysis was used to calculate combined estimates.
For pneumonia, combined adjusted odds ratios (ORs) were elevated and statistically significant for all pollutants except PM2.5 (e.g., OR=1.30; 95% CI: 1.02, 1.65 per 10-μg/m3 increase in NO2 and OR=1.76; 95% CI: 1.00, 3.09 per 10-μg/m3 PM10). For otitis media and croup, results were generally null across all analyses except for NO2 and otitis media (OR=1.09; 95% CI: 1.02, 1.16 per 10-μg/m3).
Our meta-analysis of 10 European birth cohorts within the ESCAPE project found consistent evidence for an association between air pollution and pneumonia in early childhood, and some evidence for an association with otitis media.
Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides ...(NO x ) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R 2) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R 2 ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R 2 under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.
Prenatal exposure to air pollutants has been suggested as a possible etiologic factor for the occurrence of autism spectrum disorder.
We aimed to assess whether prenatal air pollution exposure is ...associated with childhood autistic traits in the general population.
Ours was a collaborative study of four European population-based birth/child cohorts-CATSS (Sweden), Generation R (the Netherlands), GASPII (Italy), and INMA (Spain). Nitrogen oxides (NO2, NOx) and particulate matter (PM) with diameters of ≤ 2.5 μm (PM2.5), ≤ 10 μm (PM10), and between 2.5 and 10 μm (PM(coarse)), and PM2.5 absorbance were estimated for birth addresses by land-use regression models based on monitoring campaigns performed between 2008 and 2011. Levels were extrapolated back in time to exact pregnancy periods. We quantitatively assessed autistic traits when the child was between 4 and 10 years of age. Children were classified with autistic traits within the borderline/clinical range and within the clinical range using validated cut-offs. Adjusted cohort-specific effect estimates were combined using random-effects meta-analysis.
A total of 8,079 children were included. Prenatal air pollution exposure was not associated with autistic traits within the borderline/clinical range (odds ratio = 0.94; 95% CI: 0.81, 1.10 per each 10-μg/m3 increase in NO2 pregnancy levels). Similar results were observed in the different cohorts, for the other pollutants, and in assessments of children with autistic traits within the clinical range or children with autistic traits as a quantitative score.
Prenatal exposure to NO2 and PM was not associated with autistic traits in children from 4 to 10 years of age in four European population-based birth/child cohort studies.
Guxens M, Ghassabian A, Gong T, Garcia-Esteban R, Porta D, Giorgis-Allemand L, Almqvist C, Aranbarri A, Beelen R, Badaloni C, Cesaroni G, de Nazelle A, Estarlich M, Forastiere F, Forns J, Gehring U, Ibarluzea J, Jaddoe VW, Korek M, Lichtenstein P, Nieuwenhuijsen MJ, Rebagliato M, Slama R, Tiemeier H, Verhulst FC, Volk HE, Pershagen G, Brunekreef B, Sunyer J. 2016. Air pollution exposure during pregnancy and childhood autistic traits in four European population-based cohort studies: the ESCAPE Project. Environ Health Perspect 124:133-140; http://dx.doi.org/10.1289/ehp.1408483.
to describe and compare the effectiveness of national and local lockdowns in controlling the spread of COVID-19.
a rapid review of published and grey literature on COVID-19 pandemic was conducted ...following predefined eligibility criteria by searching electronic databases, repositories of pre-print articles, websites and databases of international health, and research related institutions and organisations.
of 584 initially identified records up to 5 July 2020, 19 articles met the inclusion criteria and were included in the review. Most of the studies (No. 11) used the reproduction number (Rt) as a measure of effect and in all of them areduction of the estimated value at post-intervention period was found. The implementation of lockdown in 11 European countries was associated with an average 82% reduction of Rt, ranging from a posterior Rt of 0.44 (95%CI 0.26-0.61) for Norway to a posterior Rt of 0.82 (95%CI 0.73- 0.93) for Belgium. Changes in infection rates and transmission rates were estimated in 8 studies. Daily changes in infection rates ranged from -0.6% (Sweden) to -11.3% (Hubei and Guangdong provinces). Additionally, other studies reported a change in the trend of hospitalizations (Italy, Spain) and positive effects on the doubling time of cases (Hubei, China) after lockdown.
results of this rapid review suggest a positive effect of the containment measures on the spread of COVID-19 pandemic, with a major effect in countries where lockdown started early and was more restrictive. Rigorous research is warranted to evaluate which approach is the most effective in each stage of the epidemic and in specific social contexts, in particular addressing if these approaches should be implemented on the whole population or target specific risk groups.
Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the ...performance of these methods.
Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5.
The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20–40 ESCAPE monitoring sites in each area.
The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19–0.89), 0.39 (0.23–0.66) and 0.29 (0.22–0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09–0.86) for NO2; 0.58 (0.36–0.88) for PM10 and 0.58 (0.39–0.66) for PM2.5.
LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.
•We compared LUR and dispersion model exposure estimates at individual level.•We applied both methods at addresses for multiple cohorts in Europe (n=112,971).•Correlations between methods on average were better for NO2 than PM.•Both methods may be used for studies on traffic-related air pollution epidemiology.
Associations between long-term exposure to ambient particulate matter (PM) and cardiovascular (CVD) mortality have been widely recognized. However, health effects of long-term exposure to ...constituents of PM on total CVD mortality have been explored in a single study only.
The aim of this study was to examine the association of PM composition with cardiovascular mortality.
We used data from 19 European ongoing cohorts within the framework of the ESCAPE (European Study of Cohorts for Air Pollution Effects) and TRANSPHORM (Transport related Air Pollution and Health impacts — Integrated Methodologies for Assessing Particulate Matter) projects. Residential annual average exposure to elemental constituents within particle matter smaller than 2.5 and 10μm (PM2.5 and PM10) was estimated using Land Use Regression models. Eight elements representing major sources were selected a priori (copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc). Cohort-specific analyses were conducted using Cox proportional hazards models with a standardized protocol. Random-effects meta-analysis was used to calculate combined effect estimates.
The total population consisted of 322,291 participants, with 9545 CVD deaths. We found no statistically significant associations between any of the elemental constituents in PM2.5 or PM10 and CVD mortality in the pooled analysis. Most of the hazard ratios (HRs) were close to unity, e.g. for PM10 Fe the combined HR was 0.96 (0.84–1.09). Elevated combined HRs were found for PM2.5 Si (1.17, 95% CI: 0.93–1.47), and S in PM2.5 (1.08, 95% CI: 0.95–1.22) and PM10 (1.09, 95% CI: 0.90–1.32).
In a joint analysis of 19 European cohorts, we found no statistically significant association between long-term exposure to 8 elemental constituents of particles and total cardiovascular mortality.
•Few studies explored long term effects of particle composition exposure to cardiovascular mortality.•We included a large population of 322,291 subjects from 19 cohorts in 12 countries of Europe.•Standardized cohort specific analyses were conducted individually and the results were pooled in meta-analysis.•We found no significant association between elemental constituents representing major sources and cardiovascular mortality.•Positive though non-significant associations were found for S and Si.
BACKGROUND:Long-term exposure to particulate matter (PM) has been associated with increased cardiovascular morbidity and mortality but little is known about the role of the chemical composition of ...PM. This study examined the association of residential long-term exposure to PM components with incident coronary events.
METHODS:Eleven cohorts from Finland, Sweden, Denmark, Germany, and Italy participated in this analysis. 5,157 incident coronary events were identified within 100,166 persons followed on average for 11.5 years. Long-term residential concentrations of PM < 10 μm (PM10), PM < 2.5 μm (PM2.5), and a priori selected constituents (copper, iron, nickel, potassium, silicon, sulfur, vanadium, and zinc) were estimated with land-use regression models. We used Cox proportional hazard models adjusted for a common set of confounders to estimate cohort-specific component effects with and without including PM mass, and random effects meta-analyses to pool cohort-specific results.
RESULTS:A 100 ng/m³ increase in PM10 K and a 50 ng/m³ increase in PM2.5 K were associated with a 6% (hazard ratio and 95% confidence interval1.06 1.01, 1.12) and 18% (1.18 1.06, 1.32) increase in coronary events. Estimates for PM10 Si and PM2.5 Fe were also elevated. All other PM constituents indicated a positive association with coronary events. When additionally adjusting for PM mass, the estimates decreased except for K.
CONCLUSIONS:This multicenter study of 11 European cohorts pointed to an association between long-term exposure to PM constituents and coronary events, especially for indicators of road dust.
The aim of this study was to evaluate the small scale spatial variability of nitrogen dioxide (NO2) and selected VOCs (benzene, toluene, acrolein and formaldehyde) concentrations using Land Use ...Regression models (LURs) in a complex multi sources domain (64 km2), containing a mid-size airport: the Ciampino Airport, located in Ciampino, Rome, Italy.
46 diffusion tube samplers were deployed within a domain centred in the airport over two 2-weekly periods (June 2011–January 2012). GIS-derived predictor variables, with varying buffer size, were evaluated to model spatial variation of NO2, benzene, toluene, formaldehyde and acrolein annual average concentrations. The airport apportionment to air quality was investigated using a Lagrangian dispersion model (SPRAY). A stepwise selection procedure was used to develop the linear regression models. The models were validated using leave one out cross validation (LOOCV) method.
In this study, the use of LURs was found to be effective to explain spatial variability of NO2 (adjusted-R2 = 0.72), benzene (adjusted-R2 = 0.53), toluene (adjusted-R2 = 0.50) and acrolein (adjusted-R2 = 0.51), while limited power was achieved with the formaldehyde modeling (adjusted-R2 = 0.24).
For all pollutants LURs output showed that the small scale spatial variability was mainly explained by local traffic. The airport contribution to the observed spatial variability was adequately quantified only for acrolein (0.43 (±0.69) μg/m3 in an area of about 6 km2, SW located to the airport runway), while for NO2 and formaldehyde, only a little portion of the spatial variability in a limited portion of the study domain was attributable to airport related emissions.
•NO2 and VOC's land use regression models were developed near Ciampino airport, Rome.•NO2, benzene, toluene, formaldehyde and acrolein were measured by passive sampling.•NO2, benzene, toluene and acrolein LUR models performed well.•Limited power was achieved with the formaldehyde modeling.•A little airport contribution was estimated for acrolein, NO2 and formaldheyde.
to geocode all residence addresses from Lazio Health Information System in order to obtain a geographical regional database.
a semiautomatic and multistep geocoding procedure using several tools and ...software.
all residence addresses of resident population of Lazio Region (Central Italy) in 2020.
geographic coordinates at residence addresses and accuracy level of geocoding procedure for more than 1 million of addresses.
the 99% of residence addresses in the Lazio Region have been geocoded thanks to the purposed procedure; almost 94% of the addresses have been geocoded with a good level of accuracy (more than 56% at civic number level). In the province of Rome, the percentage of addresses geocoded with a good level of accuracy is higher (97.1%), while in the province of Rieti and Frosinone is lower (82.7% and 84.2%, respectively).
this method is useful to obtain accurate geographic coordinates of residences of the entire regional population. This database will be useful for several epidemiological studies in the Region.
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