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1.
Sci Total Environ ; 804: 150091, 2021 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-34517316

RESUMO

BACKGROUND: Ambient air pollution exposure has been associated with higher mortality risk in numerous studies. We assessed potential variability in the magnitude of this association for non-accidental, cardiovascular disease, respiratory disease, and lung cancer mortality in a country-wide administrative cohort by exposure assessment method and by adjustment for geographic subdivisions. METHODS: We used the Belgian 2001 census linked to population and mortality register including nearly 5.5 million adults aged ≥30 (mean follow-up: 9.97 years). Annual mean concentrations for fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC) and ozone (O3) were assessed at baseline residential address using two exposure methods; Europe-wide hybrid land use regression (LUR) models [100x100m], and Belgium-wide interpolation-dispersion (RIO-IFDM) models [25x25m]. We used Cox proportional hazards models with age as the underlying time scale and adjusted for various individual and area-level covariates. We further adjusted main models for two different area-levels following the European Nomenclature of Territorial Units for Statistics (NUTS); NUTS-1 (n = 3), or NUTS-3 (n = 43). RESULTS: We found no consistent differences between both exposure methods. We observed most robust associations with lung cancer mortality. Hazard Ratios (HRs) per 10 µg/m3 increase for NO2 were 1.060 (95%CI 1.042-1.078) [hybrid LUR] and 1.040 (95%CI 1.022-1.058) [RIO-IFDM]. Associations with non-accidental, respiratory disease and cardiovascular disease mortality were generally null in main models but were enhanced after further adjustment for NUTS-1 or NUTS-3. HRs for non-accidental mortality per 5 µg/m3 increase for PM2.5 for the main model using hybrid LUR exposure were 1.023 (95%CI 1.011-1.035). After including random effects HRs were 1.044 (95%CI 1.033-1.057) [NUTS-1] and 1.076 (95%CI 1.060-1.092) [NUTS-3]. CONCLUSION: Long-term air pollution exposure was associated with higher lung cancer mortality risk but not consistently with the other studied causes. Magnitude of associations varied by adjustment for geographic subdivisions, area-level socio-economic covariates and less by exposure assessment method.

2.
BMJ ; 374: n1904, 2021 09 01.
Artigo em Inglês | MEDLINE | ID: mdl-34470785

RESUMO

OBJECTIVE: To investigate the associations between air pollution and mortality, focusing on associations below current European Union, United States, and World Health Organization standards and guidelines. DESIGN: Pooled analysis of eight cohorts. SETTING: Multicentre project Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE) in six European countries. PARTICIPANTS: 325 367 adults from the general population recruited mostly in the 1990s or 2000s with detailed lifestyle data. Stratified Cox proportional hazard models were used to analyse the associations between air pollution and mortality. Western Europe-wide land use regression models were used to characterise residential air pollution concentrations of ambient fine particulate matter (PM2.5), nitrogen dioxide, ozone, and black carbon. MAIN OUTCOME MEASURES: Deaths due to natural causes and cause specific mortality. RESULTS: Of 325 367 adults followed-up for an average of 19.5 years, 47 131 deaths were observed. Higher exposure to PM2.5, nitrogen dioxide, and black carbon was associated with significantly increased risk of almost all outcomes. An increase of 5 µg/m3 in PM2.5 was associated with 13% (95% confidence interval 10.6% to 15.5%) increase in natural deaths; the corresponding figure for a 10 µg/m3 increase in nitrogen dioxide was 8.6% (7% to 10.2%). Associations with PM2.5, nitrogen dioxide, and black carbon remained significant at low concentrations. For participants with exposures below the US standard of 12 µg/m3 an increase of 5 µg/m3 in PM2.5 was associated with 29.6% (14% to 47.4%) increase in natural deaths. CONCLUSIONS: Our study contributes to the evidence that outdoor air pollution is associated with mortality even at low pollution levels below the current European and North American standards and WHO guideline values. These findings are therefore an important contribution to the debate about revision of air quality limits, guidelines, and standards, and future assessments by the Global Burden of Disease.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , Doenças Cardiovasculares/mortalidade , Exposição Ambiental/efeitos adversos , Doenças não Transmissíveis/mortalidade , Europa (Continente) , Humanos
4.
Lancet Planet Health ; 5(9): e620-e632, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34508683

RESUMO

BACKGROUND: Long-term exposure to outdoor air pollution increases the risk of cardiovascular disease, but evidence is unclear on the health effects of exposure to pollutant concentrations lower than current EU and US standards and WHO guideline limits. Within the multicentre study Effects of Low-Level Air Pollution: A Study in Europe (ELAPSE), we investigated the associations of long-term exposures to fine particulate matter (PM2·5), nitrogen dioxide (NO2), black carbon, and warm-season ozone (O3) with the incidence of stroke and acute coronary heart disease. METHODS: We did a pooled analysis of individual data from six population-based cohort studies within ELAPSE, from Sweden, Denmark, the Netherlands, and Germany (recruited 1992-2004), and harmonised individual and area-level variables between cohorts. Participants (all adults) were followed up until migration from the study area, death, or incident stroke or coronary heart disease, or end of follow-up (2011-15). Mean 2010 air pollution concentrations from centrally developed European-wide land use regression models were assigned to participants' baseline residential addresses. We used Cox proportional hazards models with increasing levels of covariate adjustment to investigate the association of air pollution exposure with incidence of stroke and coronary heart disease. We assessed the shape of the concentration-response function and did subset analyses of participants living at pollutant concentrations lower than predefined values. FINDINGS: From the pooled ELAPSE cohorts, data on 137 148 participants were analysed in our fully adjusted model. During a median follow-up of 17·2 years (IQR 13·8-19·5), we observed 6950 incident events of stroke and 10 071 incident events of coronary heart disease. Incidence of stroke was associated with PM2·5 (hazard ratio 1·10 [95% CI 1·01-1·21] per 5 µg/m3 increase), NO2 (1·08 [1·04-1·12] per 10 µg/m3 increase), and black carbon (1·06 [1·02-1·10] per 0·5 10-5/m increase), whereas coronary heart disease incidence was only associated with NO2 (1·04 [1·01-1·07]). Warm-season O3 was not associated with an increase in either outcome. Concentration-response curves indicated no evidence of a threshold below which air pollutant concentrations are not harmful for cardiovascular health. Effect estimates for PM2·5 and NO2 remained elevated even when restricting analyses to participants exposed to pollutant concentrations lower than the EU limit values of 25 µg/m3 for PM2·5 and 40 µg/m3 for NO2. INTERPRETATION: Long-term air pollution exposure was associated with incidence of stroke and coronary heart disease, even at pollutant concentrations lower than current limit values. FUNDING: Health Effects Institute.

5.
Int J Cancer ; 149(11): 1887-1897, 2021 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-34278567

RESUMO

Particulate matter air pollution and diesel engine exhaust have been classified as carcinogenic for lung cancer, yet few studies have explored associations with liver cancer. We used six European adult cohorts which were recruited between 1985 and 2005, pooled within the "Effects of low-level air pollution: A study in Europe" (ELAPSE) project, and followed for the incidence of liver cancer until 2011 to 2015. The annual average exposure to nitrogen dioxide (NO2 ), particulate matter with diameter <2.5 µm (PM2.5 ), black carbon (BC), warm-season ozone (O3 ), and eight elemental components of PM2.5 (copper, iron, zinc, sulfur, nickel, vanadium, silicon, and potassium) were estimated by European-wide hybrid land-use regression models at participants' residential addresses. We analyzed the association between air pollution and liver cancer incidence by Cox proportional hazards models adjusting for potential confounders. Of 330 064 cancer-free adults at baseline, 512 developed liver cancer during a mean follow-up of 18.1 years. We observed positive linear associations between NO2 (hazard ratio, 95% confidence interval: 1.17, 1.02-1.35 per 10 µg/m3 ), PM2.5 (1.12, 0.92-1.36 per 5 µg/m3 ), and BC (1.15, 1.00-1.33 per 0.5 10-5 /m) and liver cancer incidence. Associations with NO2 and BC persisted in two-pollutant models with PM2.5 . Most components of PM2.5 were associated with the risk of liver cancer, with the strongest associations for sulfur and vanadium, which were robust to adjustment for PM2.5 or NO2 . Our study suggests that ambient air pollution may increase the risk of liver cancer, even at concentrations below current EU standards.

6.
Sci Total Environ ; 781: 146739, 2021 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-33798874

RESUMO

Biomass burning (BB) including forest, bush, prescribed fires, agricultural fires, residential wood combustion, and power generation has long been known to affect climate, air quality and human health. With this work we supply a systematic review on the health effects of BB emissions in the framework of the WHO activities on air pollution. We performed a literature search of online databases (PubMed, ISI, and Scopus) from year 1980 up to 2020. A total of 81 papers were considered as relevant for mortality and morbidity effects. High risk of bias was related with poor estimation of BB exposure and lack of adjustment for important confounders. PM10 and PM2.5 concentrations originating from BB were associated with all-cause mortality: the meta-analytical estimate was equal to 1.31% (95% CI 0.71, 1.71) and 1.92% (95% CI -1.19, 5.03) increased mortality per each 10 µg m-3 increase of PM10 and PM2.5, respectively. Regarding cardiovascular mortality 8 studies reported quantitative estimates. For smoky days and for each 10 µg m-3 increase in PM2.5 concentrations, the risk of cardiovascular mortality increased by 4.45% (95% CI 0.96, 7.95) and by 3.30% (95% CI -1.97, 8.57), respectively. Fourteen studies evaluated whether respiratory morbidity was adversely related to PM2.5 (9 studies) or PM10 (5 studies) originating from BB. All found positive associations. The pooled effect estimates were 4.10% (95% CI 2.86, 5.34) and 4.83% (95% CI 0.06, 9.60) increased risk of total respiratory admissions/emergency visits, per 10 µg m-3 increases in PM2.5 and PM10, respectively. Regarding cardiovascular morbidity, sixteen studies evaluated whether this was adversely related to PM2.5 (10 studies) or PM10 (6 studies) originating from BB. They found both positive and negative results, with summary estimates equal to 3.68% (95% CI -1.73, 9.09) and 0.93% (95% CI -0.18, 2.05) increased risk of total cardiovascular admissions/emergency visits, per 10 µg m-3 increases in PM2.5 and PM10, respectively. To conclude, a significant number of studies indicate that BB exposure is associated with all-cause and cardiovascular mortality and respiratory morbidity.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Biomassa , Exposição Ambiental/análise , Humanos , Material Particulado/efeitos adversos , Material Particulado/análise , Fumaça
7.
Environ Health Perspect ; 129(4): 47009, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33844598

RESUMO

BACKGROUND: Inconsistent associations between long-term exposure to particles with an aerodynamic diameter ≤2.5 µm [fine particulate matter (PM2.5)] components and mortality have been reported, partly related to challenges in exposure assessment. OBJECTIVES: We investigated the associations between long-term exposure to PM2.5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM2.5 components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms. METHODS: We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985-2005). Residential exposure to 2010 annual average concentration of eight PM2.5 components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a 100×100 m scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for PM2.5 mass and nitrogen dioxide (NO2) separately. RESULTS: We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RF-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both PM2.5 and NO2. HRs only remained (almost) significant for RF-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR- and RF-modeled exposures, respectively, per 2 ng/m3, adjusting for PM2.5 mass. Associations with cause-specific mortality were less consistent in two-pollutant models. CONCLUSION: Long-term exposure to V in PM2.5 was most consistently associated with increased mortality. Associations for the other components were weaker for exposure modeled with RF than SLR in two-pollutant models. https://doi.org/10.1289/EHP8368.

8.
Environ Int ; 147: 106371, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33422970

RESUMO

BACKGROUND: We evaluated methods for the analysis of multi-level survival data using a pooled dataset of 14 cohorts participating in the ELAPSE project investigating associations between residential exposure to low levels of air pollution (PM2.5 and NO2) and health (natural-cause mortality and cerebrovascular, coronary and lung cancer incidence). METHODS: We applied five approaches in a multivariable Cox model to account for the first level of clustering corresponding to cohort specification: (1) not accounting for the cohort or using (2) indicator variables, (3) strata, (4) a frailty term in frailty Cox models, (5) a random intercept under a mixed Cox, for cohort identification. We accounted for the second level of clustering due to common characteristics in the residential area by (1) a random intercept per small area or (2) applying variance correction. We assessed the stratified, frailty and mixed Cox approach through simulations under different scenarios for heterogeneity in the underlying hazards and the air pollution effects. RESULTS: Effect estimates were stable under approaches used to adjust for cohort but substantially differed when no adjustment was applied. Further adjustment for the small area grouping increased the effect estimates' standard errors. Simulations confirmed identical results between the stratified and frailty models. In ELAPSE we selected a stratified multivariable Cox model to account for between-cohort heterogeneity without adjustment for small area level, due to the small number of subjects and events in the latter. CONCLUSIONS: Our study supports the need to account for between-cohort heterogeneity in multi-center collaborations using pooled individual level data.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Estudos de Coortes , Exposição Ambiental/análise , Humanos , Material Particulado/análise
9.
Environ Res ; 193: 110568, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33278469

RESUMO

BACKGROUND: An association between long-term exposure to fine particulate matter (PM2.5) and lung cancer has been established in previous studies. PM2.5 is a complex mixture of chemical components from various sources and little is known about whether certain components contribute specifically to the associated lung cancer risk. The present study builds on recent findings from the "Effects of Low-level Air Pollution: A Study in Europe" (ELAPSE) collaboration and addresses the potential association between specific elemental components of PM2.5 and lung cancer incidence. METHODS: We pooled seven cohorts from across Europe and assigned exposure estimates for eight components of PM2.5 representing non-tail pipe emissions (copper (Cu), iron (Fe), and zinc (Zn)), long-range transport (sulfur (S)), oil burning/industry emissions (nickel (Ni), vanadium (V)), crustal material (silicon (Si)), and biomass burning (potassium (K)) to cohort participants' baseline residential address based on 100 m by 100 m grids from newly developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status). RESULTS: The pooled study population comprised 306,550 individuals with 3916 incident lung cancer events during 5,541,672 person-years of follow-up. We observed a positive association between exposure to all eight components and lung cancer incidence, with adjusted HRs of 1.10 (95% CI 1.05, 1.16) per 50 ng/m3 PM2.5 K, 1.09 (95% CI 1.02, 1.15) per 1 ng/m3 PM2.5 Ni, 1.22 (95% CI 1.11, 1.35) per 200 ng/m3 PM2.5 S, and 1.07 (95% CI 1.02, 1.12) per 200 ng/m3 PM2.5 V. Effect estimates were largely unaffected by adjustment for nitrogen dioxide (NO2). After adjustment for PM2.5 mass, effect estimates of K, Ni, S, and V were slightly attenuated, whereas effect estimates of Cu, Si, Fe, and Zn became null or negative. CONCLUSIONS: Our results point towards an increased risk of lung cancer in connection with sources of combustion particles from oil and biomass burning and secondary inorganic aerosols rather than non-exhaust traffic emissions. Specific limit values or guidelines targeting these specific PM2.5 components may prove helpful in future lung cancer prevention strategies.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Neoplasias Pulmonares , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Exposição Ambiental/análise , Europa (Continente)/epidemiologia , Humanos , Incidência , Neoplasias Pulmonares/induzido quimicamente , Neoplasias Pulmonares/epidemiologia , Material Particulado/análise
10.
Environ Int ; 146: 106249, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33197787

RESUMO

BACKGROUND/AIM: Ambient air pollution has been associated with lung cancer, but the shape of the exposure-response function - especially at low exposure levels - is not well described. The aim of this study was to address the relationship between long-term low-level air pollution exposure and lung cancer incidence. METHODS: The "Effects of Low-level Air Pollution: a Study in Europe" (ELAPSE) collaboration pools seven cohorts from across Europe. We developed hybrid models combining air pollution monitoring, land use data, satellite observations, and dispersion model estimates for nitrogen dioxide (NO2), fine particulate matter (PM2.5), black carbon (BC), and ozone (O3) to assign exposure to cohort participants' residential addresses in 100 m by 100 m grids. We applied stratified Cox proportional hazards models, adjusting for potential confounders (age, sex, calendar year, marital status, smoking, body mass index, employment status, and neighborhood-level socio-economic status). We fitted linear models, linear models in subsets, Shape-Constrained Health Impact Functions (SCHIF), and natural cubic spline models to assess the shape of the association between air pollution and lung cancer at concentrations below existing standards and guidelines. RESULTS: The analyses included 307,550 cohort participants. During a mean follow-up of 18.1 years, 3956 incident lung cancer cases occurred. Median (Q1, Q3) annual (2010) exposure levels of NO2, PM2.5, BC and O3 (warm season) were 24.2 µg/m3 (19.5, 29.7), 15.4 µg/m3 (12.8, 17.3), 1.6 10-5m-1 (1.3, 1.8), and 86.6 µg/m3 (78.5, 92.9), respectively. We observed a higher risk for lung cancer with higher exposure to PM2.5 (HR: 1.13, 95% CI: 1.05, 1.23 per 5 µg/m3). This association was robust to adjustment for other pollutants. The SCHIF, spline and subset analyses suggested a linear or supra-linear association with no evidence of a threshold. In subset analyses, risk estimates were clearly elevated for the subset of subjects with exposure below the EU limit value of 25 µg/m3. We did not observe associations between NO2, BC or O3 and lung cancer incidence. CONCLUSIONS: Long-term ambient PM2.5 exposure is associated with lung cancer incidence even at concentrations below current EU limit values and possibly WHO Air Quality Guidelines.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Neoplasias Pulmonares , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Exposição Ambiental/análise , Europa (Continente)/epidemiologia , Humanos , Neoplasias Pulmonares/induzido quimicamente , Neoplasias Pulmonares/epidemiologia , Material Particulado/análise
11.
Environ Res ; 192: 110351, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33130163

RESUMO

Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 µm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 µg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/toxicidade , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Exposição Ambiental/análise , Estudos Longitudinais , Dióxido de Nitrogênio/análise , Dióxido de Nitrogênio/toxicidade , Material Particulado/análise , Material Particulado/toxicidade
12.
Eur Respir Rev ; 29(158)2020 Dec 31.
Artigo em Inglês | MEDLINE | ID: mdl-33115789

RESUMO

AIM: There is growing interest in the health effects following exposure to ambient particles with a diameter <100 nm defined as ultrafine particles (UFPs), although studies so far have reported inconsistent results. We have undertaken a systematic review and meta-analysis for respiratory hospital admissions and emergency room visits following short-term exposure to UFPs. METHODS: We searched PubMed and the Web of Science for studies published up to March 2019 to update previous reviews. We applied fixed- and random-effects models, assessed heterogeneity between cities and explored possible effect modifiers. RESULTS: We identified nine publications, reporting effects from 15 cities, 11 of which were European. There was great variability in exposure assessment, outcome measures and the exposure lags considered. Our meta-analyses did not support UFP effects on respiratory morbidity across all ages. We found consistent statistically significant associations following lag 2 exposure during the warm period and in cities with mean daily UFP concentrations <6000 particles·cm‒3, which was approximately the median of the city-specific mean levels. Among children aged 0-14 years, a 10 000 particle·cm‒3 increase in UFPs 2 or 3 days before was associated with a relative risk of 1.01 (95% CI 1.00-1.02) in respiratory hospital admissions. CONCLUSIONS: Our study indicates UFP effects on respiratory health among children, and during the warm season across all ages at longer lags. The limited evidence and the large heterogeneity of previous reports call for future exposure assessment harmonisation and expanded research.

13.
Sci Total Environ ; 724: 138102, 2020 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-32268284

RESUMO

Cities are severely affected by air pollution. Local emissions and urban structures can produce large spatial heterogeneities. We aim to improve the estimation of NO2, O3, PM2.5 and PM10 concentrations in 6 Italian metropolitan areas, using chemical-transport and machine learning models, and to assess the effect on population exposure by using information on urban population mobility. Three years (2013-2015) of simulations were performed by the Chemical-Transport Model (CTM) FARM, at 1 km resolution, fed by boundary conditions provided by national-scale simulations, local emission inventories and meteorological fields. A downscaling of daily air pollutants at higher resolution (200 m) was then carried out by means of a machine learning Random-Forest (RF) model, considering CTM and spatial-temporal predictors, such as population, land-use, surface greenness and vehicular traffic, as input. RF achieved mean cross-validation (CV) R2 of 0.59, 0.72, 0.76 and 0.75 for NO2, PM10, PM2.5 and O3, respectively, improving results from CTM alone. Mean concentration fields exhibited clear geographical gradients caused by climate conditions, local emission sources and photochemical processes. Time series of population weighted exposure (PWE) were estimated for two months of the year 2015 and for five cities, by combining population mobility data (derived from mobile phone traffic volumes data), and concentration levels from the RF model. PWE_RF metric better approximated the observed concentrations compared with the predictions from either CTM alone or CTM and RF combined, especially for pollutants exhibiting strong spatial gradients, such as NO2. 50% of the population was estimated to be exposed to NO2 concentrations between 12 and 38 µg/m3 and PM10 between 20 and 35 µg/m3. This work supports the potential of machine learning methods in predicting air pollutant levels in urban areas at high spatial and temporal resolutions.

14.
Thromb Res ; 190: 52-57, 2020 06.
Artigo em Inglês | MEDLINE | ID: mdl-32302781

RESUMO

BACKGROUND: Short-term exposure to air pollution increases the risk of cardiovascular mortality and morbidity but little evidence is available on pollution effects on venous thromboembolism (VTE), a common vascular disease. METHODS: We conducted a case-crossover analysis of all urgent hospitalizations for deep vein thrombosis (DVT) or pulmonary embolism (PE) among patients >35 years during the period 2006 to 2017 in Rome (Italy). We examined whether 1) short-term exposure to particulate matter with aerodynamic diameter <2.5 µg (PM2.5) increases the risk of hospitalization for DVT or PE, and 2) if the associations are modified by the period of the year (warm and cold seasons), sex, age and comorbidity. RESULTS: We found that short-term exposure to PM2.5 was associated with an increase of PE hospitalization risk of during the warm season (April to September) of 19.6% (95% confidence intervals: 8.3, 31%) per 10 µg/m3, while no statistically significant effects were displayed during the cold season or the whole year or for DVT hospitalizations. The effect of PM2.5 remained significant (%change: 21.3; 95%CI: 5.4, 39.5) after adjustment for nitrogen dioxide (NO2) co-exposure (a marker of traffic sources) and when limiting to primary diagnosis of PE (%change: 19.1; 95%CI: 4.2, 36.1). Age, sex and comorbid conditions did not modify the association. CONCLUSIONS: Our results suggested a positive association between short-term exposure to PM2.5 and pulmonary embolism during the warm period of the year while no evidence emerged for deep vein thrombosis.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Tromboembolia Venosa , Poluentes Atmosféricos/efeitos adversos , Poluentes Atmosféricos/análise , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Estudos Cross-Over , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Humanos , Itália/epidemiologia , Material Particulado/efeitos adversos , Material Particulado/análise , Tromboembolia Venosa/induzido quimicamente , Tromboembolia Venosa/epidemiologia
15.
Eur J Prev Cardiol ; 2020 Nov 12.
Artigo em Inglês | MEDLINE | ID: mdl-33913491

RESUMO

AIMS: We aimed at investigating the relationship between particulate matter (PM) and daily admissions for cardiovascular diseases (CVDs) at national level in Italy. METHODS AND RESULTS: Daily numbers of cardiovascular hospitalizations were collected for all 8084 municipalities of Italy, in the period 2013-2015. A satellite-based spatiotemporal model was used to estimate daily PM10 (inhalable particles) and PM2.5 (fine particles) concentrations at 1-km2 resolution. Multivariate Poisson regression models were fit to estimate the association between daily PM and cardiovascular admissions. Flexible functions were estimated to explore the shape of the associations at low PM concentrations, also in non-urban areas. We analysed 2 154 810 acute hospitalizations for CVDs (25% stroke, 24% ischaemic heart diseases, 22% heart failure, and 5% atrial fibrillation). Relative increases of total cardiovascular admissions, per 10 µg/m3 variation in PM10 and PM2.5 at lag 0-5 (average of last 6 days since admission), were 0.55% (95% confidence intervals: 0.32%, 0.77%) and 0.97% (0.67%, 1.27%), respectively. The corresponding estimates for heart failure were 1.70% (1.28%, 2.13%) and 2.66% (2.09%, 3.23%). We estimated significant effects of PM10 and PM2.5 also on ischaemic heart diseases, myocardial infarction, atrial fibrillation, and ischaemic stroke. Associations were similar between less and more urbanized areas, and persisted even at low concentrations, e.g. below WHO guidelines. CONCLUSION: PM was robustly associated with peaks in daily cardiovascular admissions, especially for heart failure, both in large cities and in less urbanized areas of Italy. Current WHO Air Quality Guidelines for PM10 and PM2.5 are not sufficient to protect public health.

16.
Epidemiol Prev ; 44(5-6 Suppl 2): 33-41, 2020.
Artigo em Italiano | MEDLINE | ID: mdl-33412792

RESUMO

BACKGROUND: the ability to implement effective preventive and control measures is rooted in public health surveillance to promptly identify and isolate contagious patients. OBJECTIVES: to describe some organizational aspects and resources involved in the control of COVID-19 pandemic. DESIGN: observational cross sectional study. SETTING AND PARTICIPANTS: a survey of methods and tools adopted by the competent service (Prevention department) in the Local public health units (LHU) of the regional Health services has been performed in May 2020. The survey collected data related to activities carried out during the month of April 2020 on the surveillance system for collection of suspected cases, their virological ascertainment, the isolation procedures and contact-tracing activities by means of an online questionnaire filled in by the public health structure of the regional health system. A convenience sample of Prevention departments was recruited. RESULTS: in 44 Prevention departments of 14 Regions/Autonomous Provinces (caring for 40% of the population residing in Italy), different services were swiftly engaged in pandemic response. Reports of suspected cases were about 3 times the number of confirmed cases in the same month. Local reporting form was used in 46% of the LHUs while a regional form was available in 42% of the Departments (in 9/14 Regions). In one fourth the forms were not always used and 2% had no forms for the reporting of suspected cases. Data were recorded in 52% of LHUs on local databases, while in 20% a regional database (in 7 Regions) had been created. A proportion of 11% did not record the data for further elaboration. The virological assessment with nasopharyngeal swabs out of the hospital setting was carried out on the average in 7 points in each LHU (median 5) and the average daily capacity was 350 (71 per 100,000) swabs. The rate of subjects newly tested during the month of April was of 893 per 100,000 new people. Data collected at the swabbing were recorded on a regional platform in 17 LHUs (39%) of 8 Regions. In 7% LHUs only positive specimens were recorded electronically. Local files were used in 27% LHUs. The interview with confirmed cases was carried out with a local questionnaire in 52% LHUs, while 14% stated that a standardized form was not used. The data collected about cases were recorded on a regional IT platform in 30% Departments (in 8 Regions) and in 41% data were registered only locally. For each confirmed case in April, a median of 4 contacts were identified. Only 13 (30%) Departments in 9 Regions have registered contact data on a regional database. Ten Departments (23%) have only hard copies, while 56% recorded data on local databases. About 5 health professionals for 100,000 resident population were involved in each LHU in each of the following activities as receiving reports of suspected cases, swabs collection, interviews of cases and contact identifications. CONCLUSIONS: the pandemic required rapidly a great organizational effort and great flexibility to increase response capacity, which now must be strengthened and maintained. Several different tools (forms and electronic files) have been developed in each LHU and used for the same surveillance operational processes with a loss in local efficiency. The inhomogeneous data collection and recording is an obstacle for further analyses and risk identifications and is a missed opportunity for the advancement of our knowledge on pandemic epidemiology analysis. In Italy, updating the pandemic response plans is the priority, at national, regional and local level, and the occasion to fill the gaps and to improve surveillance systems to the interruption of COVID-19 transmission.


Assuntos
COVID-19/prevenção & controle , Controle de Doenças Transmissíveis/organização & administração , Pandemias/prevenção & controle , Administração em Saúde Pública/métodos , SARS-CoV-2/isolamento & purificação , COVID-19/diagnóstico , COVID-19/epidemiologia , COVID-19/transmissão , Teste para COVID-19/estatística & dados numéricos , Controle de Doenças Transmissíveis/métodos , Busca de Comunicante , Estudos Transversais , Registros Eletrônicos de Saúde , Controle de Formulários e Registros , Geografia Médica , Pesquisas sobre Serviços de Saúde , Humanos , Itália/epidemiologia , Nasofaringe/virologia , Vigilância da População
17.
Environ Health ; 18(1): 72, 2019 08 09.
Artigo em Inglês | MEDLINE | ID: mdl-31399053

RESUMO

BACKGROUND: Few studies have explored the role of air pollution in neurodegenerative processes, especially various types of dementia. Our aim was to evaluate the association between long-term exposure to air pollution and first hospitalization for dementia subtypes in a large administrative cohort. METHODS: We selected 350,844 subjects (free of dementia) aged 65-100 years at inclusion (21/10/2001) and followed them until 31/12/2013. We selected all subjects hospitalized for the first time with primary or secondary diagnoses of various forms of dementia. We estimated the exposure at residence using land use regression models for nitrogen oxides (NOx, NO2) and particulate matter (PM) and a chemical transport model for ozone (O3). We used Cox models to estimate the association between exposure and first hospitalization for dementia and its subtypes: vascular dementia (Vd), Alzheimer's disease (Ad) and senile dementia (Sd). RESULTS: We selected 21,548 first hospitalizations for dementia (7497 for Vd, 7669 for Ad and 7833 for Sd). Overall, we observed a negative association between exposure to NO2 (10 µg/m3) and dementia hospitalizations (HR = 0.97; 95% CI: 0.96-0.99) and a positive association between exposure to O3, NOx and dementia hospitalizations, (O3: HR = 1.06; 95% CI: 1.04-1.09 per 10 µg/m3; NOx: HR = 1.01; 95% CI: 1.00-1.02 per 20 µg/m3).H. Exposure to NOx, NO2, PM2.5, and PM10 was positively associated with Vd and negatively associated with Ad. Hospitalization for Sd was positively associated with exposure to O3 (HR = 1.20; 95% CI: 1.15-1.24 per 10 µg/m3). CONCLUSIONS: Our results showed a positive association between exposure to NOx and O3 and hospitalization for dementia and a negative association between NO2 exposure and hospitalization for dementia. In the analysis by subtype, exposure to each pollutants (except O3) demonstrated a positive association with vascular dementia, while O3 exposure was associated with senile dementia. The results regarding vascular dementia are a clear indication that the brain effects of air pollution are linked with vascular damage.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , Demência/epidemiologia , Exposição Ambiental/efeitos adversos , Hospitalização/estatística & dados numéricos , Idoso , Idoso de 80 Anos ou mais , Demência/induzido quimicamente , Feminino , Humanos , Incidência , Estudos Longitudinais , Masculino , Óxidos de Nitrogênio/efeitos adversos , Ozônio/efeitos adversos , Tamanho da Partícula , Material Particulado/efeitos adversos , Cidade de Roma , Emissões de Veículos
18.
Environ Health Perspect ; 127(6): 67004, 2019 06.
Artigo em Inglês | MEDLINE | ID: mdl-31166133

RESUMO

BACKGROUND: The link between particulate matter (PM) exposure and adverse health outcomes has been widely evaluated using large cohort studies. However, the possibility of residual confounding and lack of information about the health effects of PM in rural and suburban areas are unsolved issues. OBJECTIVE: Our aim was to estimate the effect of annual PM≤10µg (PM10) exposure on cause-specific mortality in the Latium region (central Italy, of which Rome is the main city) during 2006-2012 using a difference-in-differences approach. METHODS: We estimated daily PM10 concentrations for each 1 km2 of the region from 2006 to 2012 by use of satellite data, land-use predictors, and meteorological parameters. For each of the 378 regional municipalities and each year, we averaged daily PM10 values to obtain annual mean PM10 exposures. We applied a variant of the difference-in-differences approach to estimate the association between PM10 and cause-specific mortality by focusing on within-municipality fluctuations of mortality rates and annual PM exposures around municipality means, therefore controlling by design for confounding from all spatial and temporal potential confounders. Analyses were also stratified by population size of the municipalities to obtain effect estimates in rural and suburban areas of the region. RESULTS: In the period 2006-2012, we observed deaths due to three causes: 347,699 nonaccidental; 92,787 cardiovascular; and 16,509 respiratory causes. The annual average (standard deviation, SD) PM10 concentration was 21.9 (±4.9) µg/km3 in Latium. For each 1-µg/m3 increase in annual PM10 we estimated increases of 0.8% (95% confidence intervals (CIs): 0.2%, 1.3%), 0.9% (0.0%, 1.8%), and 1.4% (-0.4%, 3.3%) in nonaccidental, cardiovascular, and respiratory mortality, respectively. Similar results were found when we excluded the metropolitan area of Rome from the analysis. Higher effects were estimated in the smaller municipalities, e.g., those with population < 5,000 inhabitants. CONCLUSION: Our study suggests a significant association of annual PM10 exposure with nonaccidental and cardiorespiratory mortality in the Latium region, even outside Rome and in suburban and rural areas. https://doi.org/10.1289/EHP3759.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Doenças Cardiovasculares/mortalidade , Mortalidade , Material Particulado/efeitos adversos , Doenças Respiratórias/mortalidade , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , Causas de Morte , Exposição Ambiental/estatística & dados numéricos , Humanos , Itália/epidemiologia , População Rural/estatística & dados numéricos , População Urbana/estatística & dados numéricos
19.
Environ Int ; 124: 170-179, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30654325

RESUMO

Particulate matter (PM) air pollution is one of the major causes of death worldwide, with demonstrated adverse effects from both short-term and long-term exposure. Most of the epidemiological studies have been conducted in cities because of the lack of reliable spatiotemporal estimates of particles exposure in nonurban settings. The objective of this study is to estimate daily PM10 (PM < 10 µm), fine (PM < 2.5 µm, PM2.5) and coarse particles (PM between 2.5 and 10 µm, PM2.5-10) at 1-km2 grid for 2013-2015 using a machine learning approach, the Random Forest (RF). Separate RF models were defined to: predict PM2.5 and PM2.5-10 concentrations in monitors where only PM10 data were available (stage 1); impute missing satellite Aerosol Optical Depth (AOD) data using estimates from atmospheric ensemble models (stage 2); establish a relationship between measured PM and satellite, land use and meteorological parameters (stage 3); predict stage 3 model over each 1-km2 grid cell of Italy (stage 4); and improve stage 3 predictions by using small-scale predictors computed at the monitor locations or within a small buffer (stage 5). Our models were able to capture most of PM variability, with mean cross-validation (CV) R2 of 0.75 and 0.80 (stage 3) and 0.84 and 0.86 (stage 5) for PM10 and PM2.5, respectively. Model fitting was less optimal for PM2.5-10, in summer months and in southern Italy. Finally, predictions were equally good in capturing annual and daily PM variability, therefore they can be used as reliable exposure estimates for investigating long-term and short-term health effects.


Assuntos
Poluentes Atmosféricos/análise , Monitoramento Ambiental , Material Particulado/análise , Aerossóis/análise , Florestas , Itália , Aprendizado de Máquina , Modelos de Interação Espacial , Estações do Ano
20.
Epidemiol Prev ; 42(5-6): 316-325, 2018.
Artigo em Italiano | MEDLINE | ID: mdl-30370733

RESUMO

OBJECTIVES: to test the validity of algorithms to identify diabetes, chronic obstructive pulmonary disease (COPD), hypertension, and hypothyroidism from routinely collected health data using information from self-reported diagnosis and laboratory or functional test. SETTING AND PARTICIPANTS: clinical or self-reported diagnosis from three surveys conducted in Lazio Region (Central Italy) between year 2010 and 2014 were assumed as gold standard and compared to the results of the algorithms application to administrative data. MAIN OUTCOME MEASURES: prevalence resulted from administrative data and from information available in the surveys were compared. Sensitivity, specificity, positive predictive value, and positive likelihood ratio of algorithms with respect to self-reported diagnosis, laboratory or functional test, assumed as gold standards, were calculated. RESULTS: we analyzed data of 7,318 subjects (1,545 for diabetes, 1,783 for COPD, 2,448 for hypertension, and 1,542 for hypothyroidism). For hypertension and hypothyroidism, we observed a higher prevalence from laboratory or functional test compared to self-reported diagnosis (54.5% vs. 44.9% and 7.5% vs. 1.5%). Sensitivity of administrative data with respect to self-reported diagnosis resulted 90.9%, 38.5%, 88.3%, and 47.8%, respectively, for diabetes, COPD, hypertension, and hypothyroidism. Respectively, specificity was 97.4%, 91.7%, 84.8% and 91.8%; positive predictive value was 70,9%, 38.1%, 82.6% and 8.1%. All values of positive likelihood ratio resulted moderate (about 5), with exception of the diabetes algorithm and the disease-specific payment exemptions register for hypertension (respectively 35.5 and 17.4). CONCLUSION: hypertension and hypothyroidism resulted markedly underdiagnosed from self-reported data. Case identification algorithms are highly specific, allowing their utilization for selection of cohort of subject affected by chronic diseases. The sub-optimal sensitivity observed for COPD and hypothyroidism could limit the utilization of the algorithms for prevalence estimation.


Assuntos
Diabetes Mellitus/diagnóstico , Hipertensão/diagnóstico , Hipotireoidismo/diagnóstico , Doença Pulmonar Obstrutiva Crônica/diagnóstico , Algoritmos , Técnicas de Laboratório Clínico/estatística & dados numéricos , Bases de Dados Factuais , Diabetes Mellitus/epidemiologia , Erros de Diagnóstico/estatística & dados numéricos , Autoavaliação Diagnóstica , Sistemas de Informação em Saúde , Humanos , Hipertensão/epidemiologia , Hipotireoidismo/epidemiologia , Itália , Doença Pulmonar Obstrutiva Crônica/epidemiologia
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