176 results found
Jephcote C, Hansell AL, Adams K, et al., 2021, Changes in air quality during COVID-19 'lockdown' in the United Kingdom, ENVIRONMENTAL POLLUTION, Vol: 272, ISSN: 0269-7491
Baudin C, Lefevre M, Babisch W, et al., 2021, The role of aircraft noise annoyance and noise sensitivity in the association between aircraft noise levels and medication use: results of a pooled-analysis from seven European countries, BMC PUBLIC HEALTH, Vol: 21
Doiron D, Bourbeau J, de Hoogh K, et al., 2021, Ambient air pollution exposure and chronic bronchitis in the Lifelines cohort., Thorax
BACKGROUND: Few large studies have assessed the relationship of long-term ambient air pollution exposure with the prevalence and incidence of symptoms of chronic bronchitis and cough. METHODS: We leveraged Lifelines cohort data on 132 595 (baseline) and 65 009 (second assessment) participants linked to ambient air pollution estimates. Logistic regression models adjusted for sex, age, educational attainment, body mass index, smoking status, pack-years smoking and environmental tobacco smoke at home were used to assess associations of air pollution with prevalence and incidence of chronic bronchitis (winter cough and sputum almost daily for ≥3 months/year), chronic cough (winter cough almost daily for ≥3 months/year) and prevalence of cough and sputum symptoms, irrespective of duration. RESULTS: Associations were seen for all pollutants for prevalent cough or sputum symptoms. However, for prevalent and incident chronic bronchitis, statistically significant associations were seen for nitrogen dioxide (NO2) and black carbon (BC) but not for fine particulate matter (PM2.5). For prevalent chronic bronchitis, associations with NO2 showed OR: 1.05 (95% CI: 1.02 to 1.08) and with BC OR: 1.06 (95% CI: 1.03 to 1.09) expressed per IQR; corresponding results for incident chronic bronchitis were NO2 OR: 1.07 (95% CI: 1.02 to 1.13) and BC OR: 1.07 (95% CI: 1.02 to 1.13). In subgroup analyses, slightly stronger associations were observed among women, never smokers and younger individuals. CONCLUSION: This is the largest analysis to date to examine cross-sectional and longitudinal associations between ambient air pollution and chronic bronchitis. NO2 and BC air pollution was associated with increased odds of prevalent and incident chronic bronchitis.
Chen Y, Hodgson S, Gulliver J, et al., 2021, Trimester effects of source-specific PM10 on birth weight outcomes in the Avon Longitudinal Study of Parents and Children (ALSPAC), Environmental Health, Vol: 1, ISSN: 1476-069X
BackgroundEvidence suggests that exposure to particulate matter with aerodynamic diameter less than 10 μm (PM10) is associated with reduced birth weight, but information is limited on the sources of PM10 and exposure misclassification from assigning exposures to place of residence at birth.MethodsTrimester and source-specific PM10 exposures (PM10 from road source, local non-road source, and total source) in pregnancy were estimated using dispersion models and a full maternal residential history for 12,020 births from the Avon longitudinal study of parents and children (ALSPAC) cohort in 1990–1992 in the Bristol area. Information on birth outcomes were obtained from birth records. Maternal sociodemographic and lifestyle factors were obtained from questionnaires. We used linear regression models for continuous outcomes (birth weight, head circumference (HC), and birth length (BL) and logistic regression models for binary outcomes (preterm birth (PTB), term low birth weight (TLBW) and small for gestational age (SGA)). Sensitivity analysis was performed using multiple imputation for missing covariate data.ResultsAfter adjustment, interquartile range increases in source specific PM10 from traffic were associated with 17 to 18% increased odds of TLBW in all pregnancy periods. We also found odds of TLBW increased by 40% (OR: 1.40, 95%CI: 1.12, 1.75) and odds of SGA increased by 18% (OR: 1.18, 95%CI: 1.05, 1.32) per IQR (6.54 μg/m3) increase of total PM10 exposure in the third trimester.ConclusionThis study adds to evidence that maternal PM10 exposures affect birth weight, with particular concern in relation to exposures to PM10 from road transport sources; results for total PM10 suggest greatest effect in the third trimester. Effect size estimates relate to exposures in the 1990s and are higher than those for recent studies – this may relate to reduced exposure misclassification through use of full residential history information, changes in
Cai Y, Zijlema WL, Sorgjerd EP, et al., 2020, Impact of road traffic noise on obesity measures: Observational study of three European cohorts, ENVIRONMENTAL RESEARCH, Vol: 191, ISSN: 0013-9351
Baudin C, Lefevre M, Babisch W, et al., 2020, The role of aircraft noise annoyance and noise sensitivity in the association between aircraft noise levels and hypertension risk: Results of a pooled analysis from seven European countries, ENVIRONMENTAL RESEARCH, Vol: 191, ISSN: 0013-9351
Pirani M, Mason A, Hansell A, et al., 2020, A flexible hierarchical framework for improving inference in area-referenced environmental health studies, Biometrical Journal: journal of mathematical methods in biosciences, Vol: 62, Pages: 1650-1669, ISSN: 0323-3847
Study designs where data have been aggregated by geographical areas are popular in environmental epi-demiology. These studies are commonly based on administrative databases and, providing a completespatial coverage, are particularly appealing to make inference on the entire population. However, the re-sulting estimates are often biased and difficult to interpret due to unmeasured confounders, which typicallyare not available from routinely collected data. We propose a framework to improve inference drawn fromsuch studies exploiting information derived from individual-level survey data. The latter are summarized inan area-level scalar score by mimicking at ecological-level the well-known propensity score methodology.The literature on propensity score for confounding adjustment is mainly based on individual-level studiesand assumes a binary exposure variable. Here we generalize its use to cope with area-referenced stud-ies characterized by a continuous exposure. Our approach is based upon Bayesian hierarchical structuresspecified into a two-stage design: (i) geolocated individual-level data from survey samples are up-scaled atecological-level, then the latter are used to estimate a generalizedecological propensity score(EPS) in thein-sample areas; (ii) the generalized EPS is imputed in the out-of-sample areas under different assumptionsabout the missingness mechanisms, then it is included into the ecological regression, linking the exposureof interest to the health outcome. This delivers area-level risk estimates which allow a fuller adjustment forconfounding than traditional areal studies. The methodology is illustrated by using simulations and a casestudy investigating the risk of lung cancer mortality associated with nitrogen dioxide in England (UK).
Lavigne A, Freni Sterrantino A, Fecht D, et al., 2020, A spatial joint analysis of metal constituents of ambient particulate matter and mortality in England, Environmental Epidemiology, Vol: 4, Pages: e098-e098, ISSN: 2474-7882
Background Few studies have investigated associations between metal components of particulate matter on mortality due to well-known issues of multicollinearity. Here, we analyze these exposures jointly to evaluate their associations with mortality on small area data.Methods We fit a Bayesian Profile Regression (BPR) to account for the multicollinearity in the elemental components (iron, copper and zinc) of PM10 and PM2.5. The models are developed in relation to mortality from cardiovascular and respiratory disease and lung cancer incidence in 2008-11 at small area level, for a population of 13.6 million in the London-Oxford area of England.Results From the BPR, we identified higher risks in the PM10 fraction cluster likely to represent the study area, excluding London, for cardiovascular mortality RR 1.07 (95%CI 1.02, 1.12) and for respiratory mortality RR 1.06 (95%CI 0.99, 1.31), compared to the study mean. For PM2.5 fraction, higher risks were seen for cardiovascular mortality RR 1.55 (CI 95% 1.38, 1.71) and respiratory mortality RR 1.51 (CI 95% 1.33, 1.72), likely to represent the 'highways' cluster. We did not find relevant associations for lung cancer incidence.Conclusion Our analysis showed small but not fully consistent adverse associations between health outcomes and particulate metal exposures. The BPR approach identified subpopulations with unique exposure profiles and provided information about the geographical location of these to help interpret findings.
Cai Y, Hansell AL, Granell R, et al., 2020, Prenatal, early-life and childhood exposure to air pollution and lung function: the ALSPAC cohort, American Journal of Respiratory and Critical Care Medicine, Vol: 202, Pages: 112-123, ISSN: 1073-449X
RATIONALE: Exposure to air pollution during intrauterine development and through childhood may have lasting effects on respiratory health. OBJECTIVES: To investigate lung function at ages 8 and 15 years in relation to air pollution exposures during pregnancy, infancy and childhood in a UK population-based birth cohort. METHODS: Individual exposures to source-specific particulate matter with diameter ≤10µm (PM10) during each trimester, 0-6 months, 7-12 months (1990-1993) and up to age 15 years (1991-2008) were examined in relation to %predicted Forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) at ages 8(N=5,276) and 15(N=3,446) years, usinglinear regression models adjusted for potential confounders. A profile regression model was used to identify sensitive time periods. MEASUREMENTS AND MAIN RESULTS: We did not find clear evidence for a sensitive exposure period for PM10 from road-traffic: at age 8 years, 1µg/m3 higher exposure during the first trimester was associated with lower %predicted of FEV1(-0.826, 95%CI:-1.357 to -0.296) and FVC(-0.817, 95%CI:-1.357 to -0.276), but similar associations were seen for exposures for other trimesters, 0-6 months, 7-12 months, and 0-7 years. Associations were stronger among boys, children whose mother had a lower education level or smoked during pregnancy. For PM10 from all sources, the third trimester was associated with lower %predicted of FVC (-1.312, 95%CI: -2.100 to -0.525). At age 15 years, no adverse associations were seen with lung function. CONCLUSIONS: Exposure to road-traffic PM10 during pregnancy may result in small but significant reductions in lung function at age 8 years.
Roca-Barceló A, Crabbe H, Ghosh R, et al., 2020, Temporal trends and demographic risk factors for hospital admissions due to carbon monoxide poisoning in England, Preventive Medicine, Vol: 136, ISSN: 0091-7435
Unintentional non-fire related (UNFR) carbon monoxide (CO) poisoning is a preventable cause of morbidity and mortality. Epidemiological data on UNFR CO poisoning can help monitor changes in the magnitude of this burden, particularly through comparisons of multiple countries, and to identify vulnerable sub-groups of the population which may be more at risk. Here, we collected data on age- and sex- specific number of hospital admissions with a primary diagnosis of UNFR CO poisoning in England (2002–2016), aggregated to small areas, alongside area-level characteristics (i.e. deprivation, rurality and ethnicity). We analysed temporal trends using piecewise log-linear models and compared them to analogous data obtained for Canada, France, Spain and the US. We estimated age-standardized rates per 100,000 inhabitants by area-level characteristics using the WHO standard population (2000–2025). We then fitted the Besag York Mollie (BYM) model, a Bayesian hierarchical spatial model, to assess the independent effect of each area-level characteristic on the standardized risk of hospitalization. Temporal trends showed significant decreases after 2010. Decreasing trends were also observed across all countries studied, yet France had a 5-fold higher risk. Based on 3399 UNFR CO poisoning hospitalizations, we found an increased risk in areas classified as rural (0.69, 95% CrI: 0.67; 0.80), highly deprived (1.77, 95% CrI: 1.66; 2.10) or with the largest proportion of Asian (1.15, 95% CrI: 1.03; 1.49) or Black population (1.35, 95% CrI: 1.20; 1.80). Our multivariate approach provides strong evidence for the identification of vulnerable populations which can inform prevention policies and targeted interventions.
Fecht D, Garwood K, Butters O, et al., 2020, Automation of cleaning and reconstructing residential address histories to assign environmental exposures in longitudinal studies, International Journal of Epidemiology, Vol: 49, Pages: i49-i56, ISSN: 1464-3685
Background: We have developed an open-source ALgorithm for Generating Address Exposures (ALGAE) that cleans residential address records to construct address histories and assign spatially-determined exposuresto cohort participants. The first application of this algorithm was to construct prenatal and early-life air pollution exposure for individuals of the Avon Longitudinal Study of Parents and Children (ALSPAC)in the South West of Englandusingpreviously estimated particulate matter ≤10 μm (PM10) concentrations. Methods: ALSPAC recruited 14,541 pregnant women between 1991and 1992. We assignedtrimester-specific estimated PM10exposures for 12,752 pregnancies,and first year of life exposures for 12,525births, based on maternal residence and residential mobility. Results: Average PM10exposure was32.6 μg/m3(StDev. 3.0 μg/m3) during pregnancy and 31.4 μg/m3(StDev. 2.6 μg/m3) during the first year of life. 6.7% ofwomen changedaddress during pregnancy, and 18.0% moved during first year of lifeof their infant. Exposure differences ranged from -5.3 μg/m3 to 12.4 μg/m3(up to 26% difference) during pregnancy and -7.22 μg/m3to 7.64 μg/m3(up to 27% difference) in the first year of life,when comparing estimated exposure using the address at birth and that assessedusing the complete cleaned address history. For the majority of individualsexposure changed by <5% but some relatively large changes were seen both in pregnancy and infancy.Conclusion: ALGAE provides a generic andadaptable, open-source solution to clean addresses stored in acohort contact database and assign life-stage specific exposureestimates with the potential to reduce exposure misclassification.
Hodgson S, Fecht D, Gulliver J, et al., 2020, Availability, access, analysis and dissemination of small area data, International Journal of Epidemiology, Vol: 49, Pages: i4-i14, ISSN: 1464-3685
In this era of ‘big data’, there is growing recognition of the value of environmental, health, social and demographic data for research. Open government data initiatives are growing in number and in terms of content. Remote sensing data are finding widespread use in environmental research, including in low- and middle-income settings. While our ability to study environment and health associations across countries and continents grows, data protection rules and greater patient control over the use of their data present new challenges to using health data in research. Innovative tools that circumvent the need for the physical sharing of data by supporting non-disclosive sharing of information, or that permit spatial analysis without researchers needing access to underlying patient data can be used to support analyses while protecting data confidentiality. User-friendly visualisations, allowing small area data to be seen and understood by non-expert audiences are revolutionising public and researcher interactions with data. The UK Small Area Health Statistics Unit’s Environment and Health Atlas for England and Wales, and the US National Environmental Public Health Tracking Network offer good examples. Open data facilitates user-generated outputs, and ‘mash-ups’, and user generated inputs from social media, mobile devices, and wearable tech are new data streams which will find utility in future studies, and bring novel dimensions with respect to ethical use of small area data.
Piel F, Fecht D, Hodgson S, et al., 2020, Small-area methods for investigation of environment and health, International Journal of Epidemiology, Vol: 49, Pages: 686-699, ISSN: 1464-3685
Small-area studies offer a powerful epidemiological approach to study disease patterns at the population level and assess health risks posed by environmental pollutants. They involve a public health investigation on a geographic scale (e.g. neighbourhood) with overlay of health, environmental, demographic and potential confounder data. Recent methodological advances, including Bayesian approaches, combined with fast growing computational capabilities permit more informative analyses than previously possible, including the incorporation of data at different scales, from satellites to individual-level survey information. Better data availability has widened the scope and utility of small-area studies, but also led to greater complexity, including choice of optimal study area size and extent, duration of study periods, range of covariates and confounders to be considered, and dealing with uncertainty. The availability of data from large, well-phenotyped cohorts such as UK Biobank enables the use of mixed-level study designs and the triangulation of evidence on environmental risks from small-area and individual-level studies, therefore improving causal inference, including use of linked biomarker and -omics data. As a result, there are now improved opportunities to investigate the impacts of environmental risk factors on human health, particularly for the surveillance and prevention of non-communicable diseases.
Piel FB, Parkes B, Hambly P, et al., 2020, Software application profile: the Rapid Inquiry Facility 4.0: an open access tool for environmental public health tracking, International Journal of Epidemiology, Vol: 49, Pages: i38-i48, ISSN: 0300-5771
The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters and potential environmental hazards, whether localized (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing and complex risk analysis functionalities, while accounting for confounders. The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear power plants.
Roca Barcelo A, Douglas P, Fecht D, et al., 2020, Risk of respiratory hospital admission associated with modelled concentrations of Aspergillus fumigatus from composting facilities in England, Environmental Research, Vol: 183, Pages: 1-10, ISSN: 0013-9351
Bioaerosols have been associated with adverse respiratory-related health effects and are emitted in elevated concentrations from composting facilities. We usedmodelledAspergillus fumigatusconcentrations, a good indicator for bioaerosol emissions,to assess associations with respiratory-related hospital admissions. Mean dailyAspergillus fumigatusconcentrationswere estimated for each composting site for first full year of permit issuefrom2005 onwardsto 2014 for Census Output Areas (COAs) within 4km of 76 composting facilities in England, as previously described (Williams et al. 2019). We fitted ahierarchicalgeneralized mixed modelto examine therisk of hospital admission witha primary diagnosis of(i) any respiratory condition,(ii) respiratory infections,(iii) asthma,(iv) COPD,(v)diseases due to organic dust,and (vi)Cystic Fibrosis,inrelation to quartilesof Aspergillus fumigatusconcentrations. Models included a random intercept for each COAto account for over-dispersion,nested within composting facility, on whicha random intercept was fitted to account for clusteringof the data, with adjustmentsfor age, sex, ethnicity, deprivation, tobacco sales (smoking proxy) and traffic load (as a proxy for traffic-related air pollution). Weincluded 249,748 respiratory-related and 3,163 Cystic Fibrosis hospital admissions in 9,606 COAswith a population-weighted centroid within 4 km of the 76 included composting facilities. After adjustment for confounders, no statistically significant effect was observed for any respiratory-related (Relative Risk (RR)=0.99; 95% Confidence Interval (CI)0.96–1.01)or for Cystic Fibrosis (RR=1.01; 95% CI 0.56-1.83)hospital admissions for COAs in the highest quartile of exposure. Similar results were observed across all respiratory disease sub-groups.This study does not provide evidence for increased risks of respiratory-related hospitalisationsfor those livingnearcomposting facilities.However, given the limitations in the dispersion modelling, risks
Gulliver J, Morley D, Fecht D, et al., 2020, Feasibility study for using the CNOSSOS-EU road traffic noise prediction model with low resolution inputs for exposure estimation on a Europe-wide scale, Pages: 481-486
A noise model based on the CNOSSOS-EU method was developed to estimate exposures to road traffic noise at individual address locations for studies of noise and health in European cohorts in the EU FP7 BioSHaRE project. We assessed the loss in model performance from necessarily (i.e. at national scale) using low resolution data on traffic flows, road geography and land cover. To assess the feasibility of this approach in terms of the loss of model performance, we applied CNOSSOS-EU with different combinations of high- and low-resolution inputs (e.g. high resolution road geography with low resolution land cover) and compared noise level estimates with measurements of L from 38 locations in Leicester, a medium sized city in the UK. The lowest resolution model performed reasonably well in terms of correlation [r = 0.75; p = 0.000)] but with relatively large model errors [RMSE = 4.46 dB(A)]. For a sample of postcode (zip code) locations (n=721) in Leicester, in comparing output from Model A (highest resolution) and Model F (lowest resolution), 81.8% and 72.8% of exposure estimates remained in the lowest and highest of three equal exposure categories, respectively. Aeq1hr s
Cai Y, Blangiardo M, de Hoogh K, et al., 2020, Road traffic noise, air pollution and cardiorespiratory Health in European Cohorts: A harmonised approach in the BioShare project, Pages: 137-142
Background and aims: Few studies have investigated joint effects of road traffic noise and air pollution on cardiorespiratory outcomes. This project aims to quantify the joint and separate effects of both exposures on prevalent and incident cardiovascular disease and asthma as part of the EU-funded BioSHaRE project involving five European cohorts (EPIC-Oxford, EPIC-Turin, HUNT, Lifelines, UK Biobank). Methods: Health outcomes have been ascertained by self-report (prevalence) and medical record (incidence) and retrospectively harmonised across cohorts. Residential road traffic noise exposures for each participant are estimated using a European noise model based on Common Noise Assessment Methods in Europe (CNOSSOS-EU). Road traffic air pollution estimates at home address were derived from Land Use Regression models. Cross-sectional and incident epidemiological analyses are in progress, using individual level data, virtually pooled using DataSHIELD methodology. Results: In total, 742,950 men and women are included from all five cohorts, mostly >40 years. Prevalence of self-reported myocardial infarction from these five cohorts is 2.1% (N=15,031) while prevalence of self-reported stroke is 1.4% (N=10,077). Initial pooled analysis of EPIC-Oxford, HUNT and Lifelines showed median day-time (07:00-19:00) noise estimate of 51.8 dB(A) and night-time (23:00-07:00) noise estimate of 43.5 dB(A). Correlations between noise estimates and NO are generally low (r=0.1 to 0.4). Conclusions: Pooling of individual level harmonised data from established cohorts offers the large sample sizes and exposure variations needed to investigate effects of road traffic noise and ambient air pollution on cardio-respiratory diseases. 2
Smith RB, Beevers SD, Gulliver J, et al., 2020, Impacts of air pollution and noise on risk of preterm birth and stillbirth in London, Environment International, Vol: 134, ISSN: 0160-4120
BackgroundEvidence for associations between ambient air pollution and preterm birth and stillbirth is inconsistent. Road traffic produces both air pollutants and noise, but few studies have examined these co-exposures together and none to date with all-cause or cause-specific stillbirths.ObjectivesTo analyse the relationship between long-term exposure to air pollution and noise at address level during pregnancy and risk of preterm birth and stillbirth.MethodsThe study population comprised 581,774 live and still births in the Greater London area, 2006–2010. Outcomes were preterm birth (<37 completed weeks gestation), all-cause stillbirth and cause-specific stillbirth. Exposures during pregnancy to particulate matter with diameter <2.5 μm (PM2.5) and <10 μm (PM10), ozone (O3), primary traffic air pollutants (nitrogen dioxide, nitrogen oxides, PM2.5 from traffic exhaust and traffic non-exhaust), and road traffic noise were estimated based on maternal address at birth.ResultsAn interquartile range increase in O3 exposure was associated with elevated risk of preterm birth (OR 1.15 95% CI: 1.11, 1.18, for both Trimester 1 and 2), all-cause stillbirth (Trimester 1 OR 1.17 95% CI: 1.07, 1.27; Trimester 2 OR 1.20 95% CI: 1.09, 1.32) and asphyxia-related stillbirth (Trimester 1 OR 1.22 95% CI: 1.01, 1.49). Odds ratios with the other air pollutant exposures examined were null or <1, except for primary traffic non-exhaust related PM2.5, which was associated with 3% increased odds of preterm birth (Trimester 1) and 7% increased odds stillbirth (Trimester 1 and 2) when adjusted for O3. Elevated risk of preterm birth was associated with increasing road traffic noise, but only after adjustment for certain air pollutant exposures.DiscussionOur findings suggest that exposure to higher levels of O3 and primary traffic non-exhaust related PM2.5 during pregnancy may increase risk of preterm birth and stillbirth; and a possible relationship between long-term traff
Halonen J, Hansell A, Gulliver J, et al., 2020, Associations of road traffic noise with mortality and hospital admissions in London, Pages: 119-123
Background and aims Previously published studies have found associations of road noise with hypertension, which is a risk factor for cardiovascular disease, especially for stroke. We aimed to examine the chronic effects of road traffic noise on mortality and hospital admissions for cardiovascular disease and stroke in a large general population. Methods The study population consisted of 8.61 million inhabitants in London. We assessed small-area level associations of day- (7:00-22:59) and night-time (23:00-06:59) road traffic noise with all-cause and cardiovascular mortality and cardiovascular hospital admissions in all adults (25+ years) with Poisson regression models applying the Integrated Nested Laplace Approximation (INLA) approach in the Bayesian framework. We adjusted the models for age and sex, area-level deprivation, ethnicity, smoking, air pollution and a random effect. Results Mean daytime exposure to road traffic noise was 55.6 dB. Daytime noise was associated with all-cause and cardiovascular mortality in adults; relative risks (RR) for all-cause mortality were 1.04 (95% CI 1.00-1.07) in areas with daytime road noise >60 dB vs. <55 dB. Exposure to daytime road traffic noise also increased the risk of hospital admission for stroke with RR 1.05 (95% CI 1.02-1.09) in areas >60 dB vs. <55 dB. Night-time noise was not associated with road traffic noise in adults of all ages. Conclusions This is the largest study to date to investigate environmental noise and cardiovascular disease. It suggests that road traffic noise is associated with small increased risks of all-cause mortality and cardiovascular disease.
Parkes B, Hansell AL, Ghosh RE, et al., 2020, Risk of congenital anomalies near municipal waste incinerators in England and Scotland, Retrospective population-based cohort study, Vol: 134, ISSN: 0160-4120
Background: Few studies have investigated congenital anomalies in relation to municipal waste incinerators (MWIs) and results are inconclusive. Objectives: To conduct a national investigation into the risk of congenital anomalies in babies born to mothers living within 10 km of an MWI associated with: i) modelled concentrations of PM10 as a proxy for MWI emissions more generally and; ii) proximity of residential postcode to nearest MWI, in areas in England and Scotland that are covered by a congenital anomaly register. Methods: Retrospective population-based cohort study within 10 km of 10 MWIs in England and Scotland operating between 2003 and 2010. Exposure was proximity to MWI and log of daily mean modelled ground-level particulate matter ≤10 μm diameter (PM10) concentrations. Results: Analysis included 219,486 births, stillbirths and terminations of pregnancy for fetal anomaly of which 5154 were cases of congenital anomalies. Fully adjusted odds ratio (OR) per doubling in PM10 was: 1·00 (95% CI 0·98–1·02) for all congenital anomalies; 0·99 (0·97–1·01) for all congenital anomalies excluding chromosomal anomalies. For every 1 km closer to an MWI adjusted OR was: 1·02 (1·00–1·04) for all congenital anomalies combined; 1·02 (1·00–1·04) for all congenital anomalies excluding chromosomal anomalies; and, for specific anomaly groups, 1·04 (1·01–1·08) for congenital heart defect sand 1·07 (1·02–1·12) for genital anomalies. Discussion: We found no increased risk of congenital anomalies in relation to modelled PM10 emissions, but there were small excess risks associated with congenital heart defects and genital anomalies in proximity to MWIs. These latter findings may well reflect incomplete control for confounding, but a possible causal effect cannot be excluded.
Lavigne A, Freni Sterrantino A, Liverani S, et al., 2019, Associations between metal constituents of ambient particulate matter and mortality in England; an ecological study, BMJ Open, Vol: 9, ISSN: 2044-6055
Objectives To investigate long-term associations between metal components of particulate matter and mortality and lung cancer incidenceDesign Small area (ecological) study Setting Population living in all wards (~9000 individuals per ward) in the London and Oxford area of England, comprising 13.6 million individuals Exposure and Outcome measures We used land use regression (LUR) models originally used in the Transport related Air Pollution and Health impacts – Integrated Methodologies for Assessing Particulate Matter (TRANSPHORM) study to estimate exposure to copper, iron and zinc in ambient air particulate matter. We examined associations of metal exposure with Office for National Statistics mortality data from cardiovascular (CVD) and respiratory causes and with lung cancer incidence in 2008-11.Results There were 108,478 CVD deaths, 48,483 respiratory deaths and 24,849 incident cases of lung cancer in the study period and area. Using Poisson regression models adjusted for area-level deprivation, tobacco sales and ethnicity, we found associations between cardiovascular mortality and PM2.5 copper with interdecile range (IDR-2.6-5.7 ng/m3) and IDR Relative risk (RR) 1.005 (95%CI 1.001, 1.009) and between respiratory mortality and PM10 zinc (IDR 1135-153 ng/m3) and IDR RR 1.136 (95%CI 1.010, 1.277). We did not find relevant associations for lung cancer incidence. Metal elements were highly correlated.Conclusion Our analysis showed small but not fully consistent adverse associations between mortality and particulate metal exposures likely derived from non-tailpipe road traffic emissions (brake and tyre-wear), which have previously been associated with increases in inflammatory markers in the blood.
Marks GB, Hansell AL, Johnston FH, 2019, The environment is a first order issue for lung health, INTERNATIONAL JOURNAL OF TUBERCULOSIS AND LUNG DISEASE, Vol: 23, Pages: 1239-1242, ISSN: 1027-3719
Freni Sterrantino A, Afoakwah P, Smith RB, et al., 2019, Birth weight centiles and small for gestational age by sex and ethnicity for England and Wales, Archives of Disease in Childhood, Vol: 104, Pages: 1188-1192, ISSN: 1468-2044
Objectives To construct UK Ethnic Birth Weight Centiles (UK-EBWC) for gestational age and cut-offs for small for gestational age (SGA) for England and Wales and to evaluate the SGA misclassification using the UK centiles.Design Analysis of national birth data.Participants All live singleton births in England and Wales in 2006 to 2012, as recorded by the Office for National Statistics (ONS) and birth registrations, linked with National Health Service (NHS) into Numbers for Babies (NN4B).Main Outcome Measures Both sex-specific and ethnicity-sex-specific birth weight centiles for gestational age, and ethnicity-sex-specific SGA cut-offs. Centiles were computed using the Generalized Additive Model for Location, Scale and Shape (GAMLSS). Results Our sex-specific centiles performed well and showed an agreement between the expected and observed number of births below the centiles. The ethnicity-sex-specific centiles for Black and Asian presented lower values compared to the White centiles. Comparisons of sex-specific and ethnicity-sex-specific centiles shows that use of sex-specific centiles increases the SGA diagnosed cases by 50% for Asian, 30% for South Asian (Indian, Pakistani and Bangladeshi) and 20% for Black ethnicity.Conclusions The centiles show important differences between ethnic groups, in particular the 10th centile used to define SGA. To account for these differences and to minimize misclassification of SGA, we recommend the use of customized birth weight centiles.
Baudin C, Lefevre M, Selander J, et al., 2019, Saliva cortisol in relation to aircraft noise exposure: pooled-analysis results from seven European countries, ENVIRONMENTAL HEALTH, Vol: 18
Johnson L, Thomas R, Vande Hey J, et al., 2019, Geographically distributed longitudinal nitrogen dioxide and other air pollution sensor measurements in the Avon Longitudinal Study of Parents and Children cohort catchment area, Wellcome Open Research, Vol: 4, Pages: 162-162
<ns4:p>Longitudinal cohort studies provide unique opportunities to investigate the health impact of air pollution. We aimed to enhance the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort study through the systematic collection of routinely monitored air pollution data collected by local authorities and the Department for Environment, Food and Rural Affairs (DEFRA) using a range of sensor technologies. These sensor data are in themselves not well suited for population epidemiology, rather these data are primarily used for validating and calibrating modelled air pollution concentration data over study areas. In this data note we describe the sources of routine air pollution monitoring data and detail data of pollutants including nitrogen dioxide, nitric oxide, nitrogen oxides, particulate matter, benzene and ozone collated from the local authorities that overlap the ALSPAC catchment area (Bristol, North Somerset, South Gloucestershire and part of Bath and North East Somerset).</ns4:p>
Boyd A, Thomas R, Hansell AL, et al., 2019, Data resource profile: the ALSPAC birth cohort as a platform to study the relationship of environment and health and social factors, International Journal of Epidemiology, Vol: 48, Pages: 1038-1039k, ISSN: 1464-3685
This resource profile describes the information about the physical and social environment collected within the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort. This includes spatial and temporal information gathered on three generations about: area-level built and social characteristics (e.g. density and location of fast-food outlets, crime rates within a neighbourhood); exposure measurements (e.g. air pollution concentrations, temperature records); participant-reported data directly related to the spaces and places they inhabit (e.g. neighbourhood safety, presence of damp within a home); information directly measured from participants (e.g. blood lead and total mercury concentrations, physical activity); the location information needed to link these diverse data.We describe the platform’s previous uses, strengths and weaknesses and access arrangements, emphasizing confidentiality safeguard controls. This profile highlights a particular class of ALSPAC data (with distinct access arrangements) to promote the potential for incorporating physical environment and other spatially-dependent data into research investigations.
Doiron D, de Hoogh K, Probst-Hensch N, et al., 2019, Air pollution, lung function and COPD: results from the population-based UK Biobank study, European Respiratory Journal, Vol: 54, ISSN: 0903-1936
Ambient air pollution increases the risk of respiratory mortality but evidence for impacts on lung function and chronic obstructive pulmonary disease (COPD)is less well established. The aim was toevaluatewhether ambient air pollution isassociated with lung function andCOPD, and explore potential vulnerability factors. We used UK Biobank data on 303,887 individuals aged 40-69 years, with complete covariate data and valid lung function measures. Cross-sectional analysesexamined associations ofLand Use Regression-based estimates ofparticulate matter (PM2.5, PM1035and PMcoarse) and nitrogen dioxide (NO2) concentrations withforced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), the FEV1/FVC ratio, and COPD (FEV1/FVC 37< lower limit of normal). Effect modificationwas investigated for sex, age, obesity, smoking status, household income, asthma status, and occupations previously linked to COPD.40Higher exposures to each pollutant weresignificantly associated with lower lung function. A 5 μg/m3increase in PM2.5concentrationwas associated with lower FEV1(-83.13 mL [95%CI: -92.50, -73.75]) and FVC (-62.62 mL [95%CI:-73.91, -51.32]). COPD prevalence was associated with higher concentrations of PM2.5 (OR 1.52 [95%CI: 1.,1.62], per 5 μg/m3),PM10 (OR 1.08 [95%CI: 1.00,1.16], per 5 μg/m3), andNO2(OR 1.12 [95%CI: 1.10, 1.14], per 10 μg/m3), but not with PMcoarse.Stronger lung functionassociations were 46seenfor males, individuals from lower income households,and ‘at-risk’ occupations, and higher COPD associations for obese, lower income,and non-asthmatic participants. Ambient air pollution wasassociated with lowerlung function and increased COPD prevalencein this large study.
Freni Sterrantino A, Elliott P, Blangiardo M, et al., 2019, Bayesian spatial modelling for quasi-experimental designs: an interrupted time series study of the opening of Municipal Waste Incinerators in relation to infant mortality and sex ratio, Environment International, Vol: 128, Pages: 109-115, ISSN: 0160-4120
BackgroundThere is limited evidence on potential health risks from Municipal Waste Incinerators (MWIs), and previous studies on birth outcomes show inconsistent results. Here, we evaluate whether the opening of MWIs is associated with infant mortality and sex ratio in the surrounding areas, extending the Interrupted Time Series (ITS) methodological approach to account for spatial dependencies at the small area level.MethodsWe specified a Bayesian hierarchical model to investigate the annual risks of infant mortality and sex-ratio (female relative to male) within 10 km of eight MWIs in England and Wales, during the period 1996–2012. We included comparative areas matched one-to-one of similar size and area characteristics.ResultsDuring the study period, infant mortality rates decreased overall by 2.5% per year in England. The opening of an incinerator in the MWI area was associated with −8 deaths per 100,000 infants (95% CI −62, 40) and with a difference in sex ratio of −0.004 (95% CI −0.02, 0.01), comparing the period after opening with that before, corrected for before-after trends in the comparator areas.ConclusionOur method is suitable for the analysis of quasi-experimental time series studies in the presence of spatial structure and when there are global time trends in the outcome variable. Based on our approach, we do not find evidence of an association of MWI opening with changes in risks of infant mortality or sex ratio in comparison with control areas.
Cowie CT, Garden F, Jegasothy E, et al., 2019, Comparison of model estimates from an intra-city land use regression model with a national satellite-LUR and a regional Bayesian Maximum Entropy model, in estimating NO2 for a birth cohort in Sydney, Australia, ENVIRONMENTAL RESEARCH, Vol: 174, Pages: 24-34, ISSN: 0013-9351
Shrine N, Guyatt AL, Erzurumluoglu AM, et al., 2019, New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries (vol 51, pg 481, 2019), NATURE GENETICS, Vol: 51, Pages: 1067-1067, ISSN: 1061-4036
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