Publications
140 results found
Pimpin L, Retat L, Fecht D, et al., 2018, Estimating the costs of air pollution to the National Health Service and social care: An assessment and forecast up to 2035, PLoS Medicine, Vol: 15, ISSN: 1549-1277
BACKGROUND: Air pollution damages health by promoting the onset of some non-communicable diseases (NCDs), putting additional strain on the National Health Service (NHS) and social care. This study quantifies the total health and related NHS and social care cost burden due to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) in England. METHOD AND FINDINGS: Air pollutant concentration surfaces from land use regression models and cost data from hospital admissions data and a literature review were fed into a microsimulation model, that was run from 2015 to 2035. Different scenarios were modelled: (1) baseline 'no change' scenario; (2) individuals' pollutant exposure is reduced to natural (non-anthropogenic) levels to compute the disease cases attributable to PM2.5 and NO2; (3) PM2.5 and NO2 concentrations reduced by 1 μg/m3; and (4) NO2 annual European Union limit values reached (40 μg/m3). For the 18 years after baseline, the total cumulative cost to the NHS and social care is estimated at £5.37 billion for PM2.5 and NO2 combined, rising to £18.57 billion when costs for diseases for which there is less robust evidence are included. These costs are due to the cumulative incidence of air-pollution-related NCDs, such as 348,878 coronary heart disease cases estimated to be attributable to PM2.5 and 573,363 diabetes cases estimated to be attributable to NO2 by 2035. Findings from modelling studies are limited by the conceptual model, assumptions, and the availability and quality of input data. CONCLUSIONS: Approximately 2.5 million cases of NCDs attributable to air pollution are predicted by 2035 if PM2.5 and NO2 stay at current levels, making air pollution an important public health priority. In future work, the modelling framework should be updated to include multi-pollutant exposure-response functions, as well as to disaggregate results by socioeconomic status.
Fecht D, Jones A, Hill T, et al., 2018, Inequalities in rural communities: Adapting national deprivation indices for rural settings, Journal of Public Health, Vol: 40, Pages: 419-425, ISSN: 2198-1833
BackgroundDeprivation indices have been widely used in healthcare research and planning in the United Kingdom. Existing indices, however, are dominated by characteristics of urban populations that may be less relevant in capturing the nature of rural deprivation. We explore if deprivation indices can be modified to make them more sensitive to displaying rural disadvantage in England.MethodsThe analysis focussed on the 2011 Carstairs Index (Carstairs2011) and the 2010 English Index of Multiple Deprivation (IMD2010). We removed all urban areas as identified by the Office for National Statistics Rural–Urban Area Classifications and mapped the Carstairs2011 and IMD2010 across the remaining rural areas using rural-specific quintiles.ResultsOur method was effective in displaying much greater heterogeneity in rural areas than was apparent in the original indices. We received positive feedback from Directors of Public Health who confirmed that the observed patterns mirror their experiences and first-hand knowledge on the ground.ConclusionsOur maps of Carstairs2011 and IMD2010 for rural areas might strengthen the evidence base for rural planning and service provision. The modified deprivation indices, however, were not specifically formulated for rural populations and further work is needed to explore alternative input variables to produce a more rural-specific measure of deprivation.
Tonne C, Milà C, Fecht D, et al., 2018, Socioeconomic and ethnic inequalities in exposure to air and noise pollution in London, Environment International, Vol: 115, Pages: 170-179, ISSN: 0160-4120
BACKGROUND: Transport-related air and noise pollution, exposures linked to adverse health outcomes, varies within cities potentially resulting in exposure inequalities. Relatively little is known regarding inequalities in personal exposure to air pollution or transport-related noise. OBJECTIVES: Our objectives were to quantify socioeconomic and ethnic inequalities in London in 1) air pollution exposure at residence compared to personal exposure; and 2) transport-related noise at residence from different sources. METHODS: We used individual-level data from the London Travel Demand Survey (n = 45,079) between 2006 and 2010. We modeled residential (CMAQ-urban) and personal (London Hybrid Exposure Model) particulate matter <2.5 μm and nitrogen dioxide (NO2), road-traffic noise at residence (TRANEX) and identified those within 50 dB noise contours of railways and Heathrow airport. We analyzed relationships between household income, area-level income deprivation and ethnicity with air and noise pollution using quantile and logistic regression. RESULTS: We observed inverse patterns in inequalities in air pollution when estimated at residence versus personal exposure with respect to household income (categorical, 8 groups). Compared to the lowest income group (<£10,000), the highest group (>£75,000) had lower residential NO2 (-1.3 (95% CI -2.1, -0.6) μg/m3 in the 95th exposure quantile) but higher personal NO2 exposure (1.9 (95% CI 1.6, 2.3) μg/m3 in the 95th quantile), which was driven largely by transport mode and duration. Inequalities in residential exposure to NO2 with respect to area-level deprivation were larger at lower exposure quantiles (e.g. estimate for NO2 5.1 (95% CI 4.6, 5.5) at quantile 0.15 versus 1.9 (95% CI 1.1, 2.6) at quantile 0.95), reflecting low-deprivation, high residential NO2 areas in the city centre. Air pollution exposure at residence consistently overestimated personal exposure; this overestimation varied with age
Williams ML, Beevers S, Kitwiroon N, et al., 2018, Public health air pollution impacts of pathway options to meet the 2050 UK Climate Change Act target: a modelling study, Public Health Research, Vol: 6, Pages: 1-124, ISSN: 2050-4381
BackgroundThe UK’s Climate Change Act 2008 (CCA; Great Britain. Climate Change Act 2008. Chapter 27. London: The Stationery Office; 2008) requires a reduction of 80% in carbon dioxide-equivalent emissions by 2050 on a 1990 base. This project quantified the impact of air pollution on health from four scenarios involving particulate matter of ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Two scenarios met the CCA target: one with limited nuclear power build (nuclear replacement option; NRPO) and one with no policy constraint on nuclear (low greenhouse gas). Another scenario envisaged no further climate actions beyond those already agreed (‘baseline’) and the fourth kept 2011 concentrations constant to 2050 (‘2011’).MethodsThe UK Integrated MARKAL–EFOM System (UKTM) energy system model was used to develop the scenarios and produce projections of fuel use; these were used to produce air pollutant emission inventories for Great Britain (GB) for each scenario. The inventories were then used to run the Community Multiscale Air Quality model ‘air pollution model’ to generate air pollutant concentration maps across GB, which then, combined with relationships between concentrations and health outcomes, were used to calculate the impact on health from the air pollution emitted in each scenario. This is a significant improvement on previous health impact studies of climate policies, which have relied on emissions changes. Inequalities in exposure in different socioeconomic groups were also calculated, as was the economic impact of the pollution emissions.ResultsConcentrations of NO2 declined significantly because of a high degree of electrification of the GB road transport fleet, although the NRPO scenario shows large increases in oxides of nitrogen emissions from combined heat and power (CHP) sources. Concentrations of PM2.5 show a modest decrease by 2050, which would have been larger if it had n
Pimpin L, Retat L, Fecht D, et al., 2018, Estimation of costs to the NHS and social care due to the health impacts of air pollution
Cai Y, Hansell A, Hodgson S, et al., 2018, Road traffic noise, air pollution and incident cardiovascular disease: a joint analysis of the HUNT, EPIC-Oxford and UK Biobank cohorts, Environment International, ISSN: 0160-4120
Background: This study aimed to investigate the effects of long-term exposure to road traffic noiseand air pollutionon incident cardiovascular disease (CVD)in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. Methods: In pooled complete-casesample of the three cohorts from Norway and the United Kingdom(N=355,732), 21,081 incident all CVD cases including 5,259ischemic heart disease (IHD)and 2,871cerebrovascular cases were ascertained between baseline (1993-2010)and end of follow-up (2008-2013)through medical recordlinkage. Annual mean 24-hour weighted road traffic noise(Lden) and air pollution (particulate matter with aerodynamic diameter ≤10 μm [PM10],≤2.5 μm [PM2.5]andnitrogen 39dioxide[NO2])exposure at baseline address was modelled using a simplified version of the Common Noise Assessment Methods in Europe (CNOSSOS-EU)and European-wide Land Use Regression models.Individual-level covariate data were harmonised and physically pooled across the three cohorts. Analysis was via Cox proportional hazard model with mutual adjustmentsforboth noise and air pollution andpotential confounders. Results: No significant associations were found between annual mean Ldenand incidentCVD,IHD or cerebrovascular disease in the overall populationexcept that the association withincident IHD was significantamong current-smokers.In the fully adjusted models including adjustmentfor Lden, an interquartile range (IQR) higher PM10(4.1μg/m3) or PM2.5(1.4μg/m3) was associated witha5.8% (95%CI: 2.5%-9.3%) and 3.7% (95%CI: 0.2%-7.4%) higherrisk for all incident CVD respectively. No significant associations were found between NO2and any of the CVD outcomes. Conclusions: We found suggestive evidence of a possible association between road traffic noise and incident IHD, consistent with current literature. Long-term particulate air pollution exposure, even at concentrations below current European air quality standards, w
Gulliver J, Elliott P, Hansell A, et al., 2018, Local- and regional-scale air pollution modelling (PM10) and exposure assessment for pregnancy trimesters, infancy, and childhood to age 15 years: Avon Longitudinal Study of Parents And Children (ALSPAC)., Environment International, Vol: 113, Pages: 10-19, ISSN: 0160-4120
We established air pollution modelling to study particle (PM10) exposures during pregnancy and infancy (1990–1993) through childhood and adolescence up to age ~15 years (1991–2008) for the Avon Longitudinal Study of Parents And Children (ALSPAC) birth cohort. For pregnancy trimesters and infancy (birth to 6 months; 7 to 12 months) we used local (ADMS-Urban) and regional/long-range (NAME-III) air pollution models, with a model constant for local, non-anthropogenic sources. For longer exposure periods (annually and the average of birth to age ~8 and to age ~15 years to coincide with relevant follow-up clinics) we assessed spatial contrasts in local sources of PM10 with a yearly-varying concentration for all background sources. We modelled PM10 (μg/m3) for 36,986 address locations over 19 years and then accounted for changes in address in calculating exposures for different periods: trimesters/infancy (n = 11,929); each year of life to age ~15 (n = 10,383). Intra-subject exposure contrasts were largest between pregnancy trimesters (5th to 95th centile: 24.4–37.3 μg/m3) and mostly related to temporal variability in regional/long-range PM10. PM10 exposures fell on average by 11.6 μg/m3 from first year of life (mean concentration = 31.2 μg/m3) to age ~15 (mean = 19.6 μg/m3), and 5.4 μg/m3 between follow-up clinics (age ~8 to age ~15). Spatial contrasts in 8-year average PM10 exposures (5th to 95th centile) were relatively low: 25.4–30.0 μg/m3 to age ~8 years and 20.7–23.9 μg/m3 from age ~8 to age ~15 years. The contribution of local sources to total PM10 was 18.5%–19.5% during pregnancy and infancy, and 14.4%–17.0% for periods leading up to follow-up clinics. Main roads within the study area contributed on average ~3.0% to total PM10 exposures in all periods; 9.5% of address locations were within 50 m of a main road. Exposure estimates will be used in a number of planned epidemiological studies.
Williams ML, Lott MC, Kitwiroon N, et al., 2018, The Lancet Countdown on health benefits from the UK Climate Change Act, a modelling study for Great Britain, Vol: 2, Pages: e202-e213, ISSN: 2542-5196
Background Climate change poses a dangerous and immediate threat to the health of populations in the UK and worldwide. We aimed to model different scenarios to assess the health co-benefits that result from mitigation actions. Methods In this modelling study, we combined a detailed techno-economic energy systems model (UK TIMES), air pollutant emission inventories, a sophisticated air pollution model (Community Multi-scale Air Quality), and previously published associations between concentrations and health outcomes. We used four scenarios and focused on the air pollution implications from fine particulate matter (PM2·5), nitrogen dioxide (NO2) and ozone. The four scenarios were baseline, which assumed no further climate actions beyond those already achieved and did not meet the UK's Climate Change Act (at least an 80% reduction in carbon dioxide equivalent emissions by 2050 compared with 1990) target; nuclear power, which met the Climate Change Act target with a limited increase in nuclear power; low-greenhouse gas, which met the Climate Change Act target without any policy constraint on nuclear build; and a constant scenario that held 2011 air pollutant concentrations constant until 2050. We predicted the health and economic impacts from air pollution for the scenarios until 2050, and the inequalities in exposure across different socioeconomic groups. Findings NO2 concentrations declined leading to 4 892 000 life-years saved for the nuclear power scenario and 7 178 000 life-years saved for the low-greenhouse gas scenario from 2011 to 2154. However, the associations that we used might overestimate the effects of NO2 itself. PM2·5 concentrations in Great Britain are predicted to decrease between 42% and 44% by 2050 compared with 2011 in the scenarios that met the Climate Change Act targets, especially those from road traffic and off-road machinery. These reductions in PM2·5 are tempered by a 2035 peak (and subsequent decline) in biomass (wood bu
Smith RB, Fecht D, Gulliver J, et al., 2017, Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study, BMJ, Vol: 359, ISSN: 1756-1833
Objective To investigate the relation between exposure to both air and noise pollution from road traffic and birth weight outcomes.Design Retrospective population based cohort study.Setting Greater London and surrounding counties up to the M25 motorway (2317 km2), UK, from 2006 to 2010.Participants 540 365 singleton term live births.Main outcome measures Term low birth weight (LBW), small for gestational age (SGA) at term, and term birth weight.Results Average air pollutant exposures across pregnancy were 41 μg/m3 nitrogen dioxide (NO2), 73 μg/m3 nitrogen oxides (NOx), 14 μg/m3 particulate matter with aerodynamic diameter <2.5 μm (PM2.5), 23 μg/m3 particulate matter with aerodynamic diameter <10 μm (PM10), and 32 μg/m3 ozone (O3). Average daytime (LAeq,16hr) and night-time (Lnight) road traffic A-weighted noise levels were 58 dB and 53 dB respectively. Interquartile range increases in NO2, NOx, PM2.5, PM10, and source specific PM2.5 from traffic exhaust (PM2.5 traffic exhaust) and traffic non-exhaust (brake or tyre wear and resuspension) (PM2.5 traffic non-exhaust) were associated with 2% to 6% increased odds of term LBW, and 1% to 3% increased odds of term SGA. Air pollutant associations were robust to adjustment for road traffic noise. Trends of decreasing birth weight across increasing road traffic noise categories were observed, but were strongly attenuated when adjusted for primary traffic related air pollutants. Only PM2.5 traffic exhaust and PM2.5 were consistently associated with increased risk of term LBW after adjustment for each of the other air pollutants. It was estimated that 3% of term LBW cases in London are directly attributable to residential exposure to PM2.5>13.8 μg/m3during pregnancy.Conclusions The findings suggest that air pollution from road traffic in London is adversely affecting fetal growth. The results suggest little evidence for an independent exposure-response effect of traffic related noise on b
Douglas P, Freni-Sterrantino A, Leal Sanchez M, et al., 2017, Estimating Particulate Exposure from Modern Municipal Waste Incinerators in Great Britain, Environmental science & technology, Vol: 51, Pages: 7511-7519, ISSN: 0013-936X
Municipal Waste Incineration (MWI) is regulated through the European Union Directive on Industrial Emissions (IED), but there is ongoing public concern regarding potential hazards to health. Using dispersion modeling, we estimated spatial variability in PM10 concentrations arising from MWIs at postcodes (average 12 households) within 10 km of MWIs in Great Britain (GB) in 2003-2010. We also investigated change points in PM10 emissions in relation to introduction of EU Waste Incineration Directive (EU-WID) (subsequently transposed into IED) and correlations of PM10 with SO2, NOx, heavy metals, polychlorinated dibenzo-p-dioxins/furan (PCDD/F), polycyclic aromatic hydrocarbon (PAH) and polychlorinated biphenyl (PCB) emissions. Yearly average modeled PM10 concentrations were 1.00 × 10-5 to 5.53 × 10-2 μg m-3, a small contribution to ambient background levels which were typically 6.59-2.68 × 101 μg m-3, 3-5 orders of magnitude higher. While low, concentration surfaces are likely to represent a spatial proxy of other relevant pollutants. There were statistically significant correlations between PM10 and heavy metal compounds (other heavy metals (r = 0.43, p = <0.001)), PAHs (r = 0.20, p = 0.050), and PCBs (r = 0.19, p = 0.022). No clear change points were detected following EU-WID implementation, possibly as incinerators were operating to EU-WID standards before the implementation date. Results will be used in an epidemiological analysis examining potential associations between MWIs and health outcomes.
Cai Y, Hodgson S, Blangiardo M, et al., 2017, Road traffic noise and incident cardiovascular disease: a joint analysis of HUNT, EPIC-Oxford and UK Biobank, ICBEN 2017 Proceedings
Aims: This study aimed to investigate the effects of long-term exposure to road traffic noise on incident CVD in three large cohorts: HUNT, EPIC-Oxford and UK Biobank. Methods: In a complete-case sample (N=361,699), 4,014 IHD and 2,109 cerebrovascular incident cases were ascertained between baseline (1993-2010) and end of follow-up (2008-2015) through medical record linkage. Annual mean road traffic noise exposure was modelled at baseline address. Individual-level covariate data were harmonised and data were pooled. Analyses used Cox proportional hazards model with adjustments for confounders, including air pollution. Results: For an interquartile range (IQR) (3.9 dBA) higher daytime noise, a non-significant association with incident IHD was seen (Hazard ratio (HR): 1.015, 95% Confidence Interval (CI): 0.989-1.042), fully adjusted. Statistically significant associations and interaction terms were seen in obese individuals (HR: 1.099, 95%CI: 1.029-1.174), and current-smokers (HR: 1.054, 95%CI: 1.007-1.103). No associations were found for ischemic or hemorrhagic stroke. Conclusions: Our study strengthens the evidence base for an effect of road traffic noise on incident IHD, whilst the association with incident stroke remains unclear.
Pierotti L, Collet D, Schofield S, et al., 2017, Traffic Related Air Pollution and Transplant Failure, Publisher: ELSEVIER SCI LTD, Pages: S111-S112, ISSN: 2214-1405
, 2017, Associations of night-time road traffic noise with carotid intima-media thickness and blood pressure: The Whitehall II and SABRE study cohorts, Vol: 98, Pages: 54-61, ISSN: 1873-6750
Dehbi HM, Blangiardo M, Gulliver J, et al., 2016, Air pollution and cardiovascular mortality with over 25 years follow-up: A combined analysis of two British cohorts, Environment International, Vol: 99, Pages: 275-281, ISSN: 1873-6750
BACKGROUND: Adverse effects of air pollution on cardiovascular disease (CVD) mortality are well established. There are comparatively fewer studies in Europe, and in the UK particularly, than in North America. We examined associations in two British cohorts with >25years of follow-up. METHODS: Annual average NO2, SO2 and black smoke (BS) air pollution exposure estimates for 1991 were obtained from land use regression models using contemporaneous monitoring data. From the European Study of Cohorts and Air Pollution (ESCAPE), air pollution estimates in 2010-11 were obtained for NO2, NOx, PM10, PMcoarse and PM2.5. The exposure estimates were assigned to place of residence 1989 for participants in a national birth cohort born in 1946, the MRC National Study of Health and Development (NSHD), and an adult multi-ethnic London cohort, Southall and Brent Revisited (SABRE) recruited 1988-91. The combined median follow-up was 26years. Single-pollutant competing risk models were employed, adjusting for individual risk factors. RESULTS: Elevated non-significant hazard ratios for CVD mortality were seen with 1991 BS and SO2 and with ESCAPE PM10 and PM2.5 in fully adjusted linear models. Per 10μg/m(3) increase HRs were 1.11 [95% CI: 0.76-1.61] for BS, 1.05 [95% CI: 0.91-1.22] for SO2, 1.16 [95% CI: 0.70-1.92] for PM10 and 1.30 [95% CI: 0.39-4.34] for PM2.5, with largest effects seen in the fourth quartile of BS and PM2.5 compared to the first with HR 1.24 [95% CI: 0.91-1.61] and 1.21 [95% CI: 0.88-1.66] respectively. There were no consistent associations with other ESCAPE pollutants, or with 1991 NO2. Modelling using Cox regression led to similar results. CONCLUSION: Our results support a detrimental long-term effect for air pollutants on cardiovascular mortality.
Bakolis I, Kelly R, Fecht D, et al., 2016, Protective Effects of Smoke-free Legislation on Birth Outcomes in England: A Regression Discontinuity Design, Epidemiology, Vol: 27, Pages: 810-818, ISSN: 1531-5487
Background: Environmental tobacco smoke has an adverse impact on preterm birth and birthweight. England introduced a new law to make virtually all enclosed public places andworkplaces smoke free on July 1 2007. We investigated the effect of smoke-free legislation onbirth outcomes in England using Hospital Episode Statistics (HES) maternity data.Methods: We used regression discontinuity, a quasi-experimental study design, which canfacilitate valid causal inference, to analyse short-term effects of smoke-free legislation on birthweight, low birth weight, gestational age, preterm birth and small for gestational age.Results: We analysed 1,800,906 pregnancies resulting in singleton live-births in Englandbetween January 1 2005 and December 31 2009. In the one to five months following theintroduction of the smoking-free legislation, for those entering their third trimester, the risk oflow birth weight decreased by between 8% (95% CI: 4%-12%) and 14% (95% CI: 5%-23%),very low birth weight between 28% (95% CI: 19%-36%) and 32% (95% CI: 21%-41%), pretermbirth between 4% (95% CI: 1%-8%) and 9% (95% CI: 2%-16%), and small for gestational agebetween 5% (95% CI: 2%-8%) and 9% (95% CI: 2%-15%). The impact of the smoke-freelegislation varied by maternal age, deprivation, ethnicity and region.Conclusions: The introduction of smoke-free legislation in England had an immediate beneficialimpact on birth outcomes overall, although this benefit was not observed across all age, ethnic, ordeprivation groups.
Hallett TB, Anderson S-J, Asante CA, et al., 2016, Evaluation of geospatial methods to generate subnational HIV prevalence estimates for local level planning, AIDS, Vol: 30, Pages: 1467-1474, ISSN: 0269-9370
Objective: There is evidence of substantial subnational variation in the HIV epidemic. However, robust spatial HIV data are often only available at high levels of geographic aggregation and not at the finer resolution needed for decision making. Therefore, spatial analysis methods that leverage available data to provide local estimates of HIV prevalence may be useful. Such methods exist but have not been formally compared when applied to HIV.Design/methods: Six candidate methods – including those used by the Joint United Nations Programme on HIV/AIDS to generate maps and a Bayesian geostatistical approach applied to other diseases – were used to generate maps and subnational estimates of HIV prevalence across three countries using cluster level data from household surveys. Two approaches were used to assess the accuracy of predictions: internal validation, whereby a proportion of input data is held back (test dataset) to challenge predictions; and comparison with location-specific data from household surveys in earlier years.Results: Each of the methods can generate usefully accurate predictions of prevalence at unsampled locations, with the magnitude of the error in predictions similar across approaches. However, the Bayesian geostatistical approach consistently gave marginally the strongest statistical performance across countries and validation procedures.Conclusions: Available methods may be able to furnish estimates of HIV prevalence at finer spatial scales than the data currently allow. The subnational variation revealed can be integrated into planning to ensure responsiveness to the spatial features of the epidemic. The Bayesian geostatistical approach is a promising strategy for integrating HIV data to generate robust local estimates.
Gulliver J, de Hoogh K, Hoek G, et al., 2016, Back-extrapolated and year-specific NO2 land use regression models for Great Britain - Do they yield different exposure assessment?, Environment International, Vol: 92-93, Pages: 202-209, ISSN: 1873-6750
Robust methods to estimate historic population air pollution exposures are important tools for epidemiological studies evaluating long-term health effects. We developed land use regression (LUR) models for NO2 exposure in Great Britain for 1991 and explored whether the choice of year-specific or back-extrapolated LUR yields 1) similar LUR variables and model performance, and 2) similar national and regional address-level and small-area concentrations. We constructed two LUR models for 1991using NO2 concentrations from the diffusion tube monitoring network, one using 75% of all available measurement sites (that over-represent industrial areas), and the other using 75% of a subset of sites proportionate to population by region to study the effects of monitoring site selection bias. We compared, using the remaining (hold-out) 25% of monitoring sites, the performance of the two 1991 models with back-extrapolation of a previously published 2009 model, developed using NO2 concentrations from automatic chemiluminescence monitoring sites and predictor variables from 2006/2007. The 2009 model was back-extrapolated to 1991 using the same predictors (1990 & 1995) used to develop 1991 models. The 1991 models included industrial land use variables, not present for 2009. The hold-out performance of 1991 models (mean-squared-error-based-R2: 0.62–0.64) was up to 8% higher and ~ 1 μg/m3 lower in root mean squared error than the back-extrapolated 2009 model, with best performance from the subset of sites representing population exposures. Year-specific and back-extrapolated exposures for residential addresses (n = 1.338,399) and small areas (n = 10.518) were very highly linearly correlated for Great Britain (r > 0.83). This study suggests that year-specific model for 1991 and back-extrapolation of the 2009 LUR yield similar exposure assessment.
Douglas P, Bakolis I, Fecht D, et al., 2016, Respiratory hospital admission risk near large composting facilities, International Journal of Hygiene and Environmental Health, Vol: 219, Pages: 372-379, ISSN: 1618-131X
BackgroundLarge-scale composting can release bioaerosols in elevated quantities, but there are few studies of health effects on nearby communitiesMethodsA cross-sectional ecological small area design was used to examine risk of respiratory hospital admissions within 2500 m of all 148 English large-scale composting facilities in 2008–10. Statistical analyses used a random intercept Poisson regression model at Census Output Area (COA) level (mean population 310). Models were adjusted for age, sex, deprivation and tobacco sales.ResultsAnalysing 34,963 respiratory hospital admissions in 4656COAs within 250–2500 m of a site, there were no significant trends using pre-defined distance bands of >250m-750m, >750–1500 m and >1500-2500m. Using a continuous measure of distance, there was a small non-statistically significant (p = 0.054) association with total respiratory admissions corresponding to a 1.5% (95% CI: 0.0–2.9%) decrease in risk if moving from 251 m to 501m. There were no significant associations for subgroups of respiratory infections, asthma or chronic obstructive pulmonary disease.ConclusionThis national study does not provide evidence for increased risks of respiratory hospital admissions in those living beyond 250 m of an outdoor composting area perimeter. Further work using better measures of exposure and exploring associations with symptoms and disease prevalence, especially in vulnerable groups, is recommended to support regulatory approaches.
Fecht D, Fortunato L, Morley D, et al., 2016, Associations between urban metrics and mortality rates in England, Environmental Health, Vol: 15, ISSN: 1832-3367
BackgroundSeventy-five percent of the population in Europe live in urban areas and analysing the effectsof urban form on the health of the urban population is of great public health interest. Notmuch is known, however, on the effects of urban form on the health of city dwellers. Thisstudy uses a novel approach to investigate whether associations exist between differentmeasures of urban form and mortality risks in cities in England.MethodsWe conducted an ecological, cross-sectional study for urban areas in England with more than100,000 residents (n = 50) and included all registered premature deaths (<65 years) between1st January 2002 and 31th December 2009. To describe and categorise urban form wequantified the distribution and density of population, land cover and transport networks andmeasures of geographical characteristics. We used Poisson regression models to examineassociations between the measures of urban form and age-standardised risks of deaths fromall causes, cardiovascular disease, and traffic accidents after adjustment for socioeconomicstatus and smoking. Analysis was stratified by gender to explore differential associationsbetween females and males.ResultsThere were a total of 200,200 premature deaths during the study period (Females: 37%;Males: 63%). Transport network patterns were associated with overall and cardiovascularmortality rates in cities. We saw 12% higher mortality risk after adjustment in cities with highjunction density compared to cities with low density [Females: RR 1.12 (95% CI 1.10 –1.15); Males: RR 1.12 (95% CI 1.10 -1.14)]; the risk was slightly higher for cardiovascularmortality [Females: RR 1.16 (95% CI 1.10 – 1.22); Males: RR 1.12 (95% CI 1.09 – 1.16)].Associations between mortality and population patterns were of similar magnitude [Females: 3RR 1.10 (95% CI 1.09 – 1.13); Males: RR 1.09 (95% CI 1.07 -1.10)]; associations betweenmortality and land cover patterns were inconclusive.ConclusionsWe found an a
Fecht D, Hansell A, Morley D, et al., 2016, Spatial and temporal associations of road traffic noise and air pollution in London: Implications for epidemiological studies, Environment International, Vol: 88, Pages: 235-242, ISSN: 0160-4120
Road traffic gives rise to noise and air pollution exposures, both of which are associated with adverse health effects especially for cardiovascular disease, but mechanisms may differ. Understanding the variability in correlations between these pollutants is essential to understand better their separate and joint effects on human health.We explored associations between modelled noise and air pollutants using different spatial units and area characteristics in London in 2003–2010.We modelled annual average exposures to road traffic noise (LAeq,24 h, Lden, LAeq,16 h, Lnight) for ~ 190,000 postcode centroids in London using the UK Calculation of Road Traffic Noise (CRTN) method. We used a dispersion model (KCLurban) to model nitrogen dioxide, nitrogen oxide, ozone, total and the traffic-only component of particulate matter ≤ 2.5 μm and ≤ 10 μm. We analysed noise and air pollution correlations at the postcode level (~ 50 people), postcodes stratified by London Boroughs (~ 240,000 people), neighbourhoods (Lower layer Super Output Areas) (~ 1600 people), 1 km grid squares, air pollution tertiles, 50 m, 100 m and 200 m in distance from major roads and by deprivation tertiles.Across all London postcodes, we observed overall moderate correlations between modelled noise and air pollution that were stable over time (Spearman's rho range: | 0.34–0.55 |). Correlations, however, varied considerably depending on the spatial unit: largest ranges were seen in neighbourhoods and 1 km grid squares (both Spearman's rho range: | 0.01–0.87 |) and was less for Boroughs (Spearman's rho range: | 0.21–0.78 |). There was little difference in correlations between exposure tertiles, distance from road or deprivation tertiles.Associations between noise and air pollution at the relevant geographical unit of analysis need to be carefully considered in any epidemiological analysis, in particular in complex urban areas. Low correlations near roads, however, sugges
Halonen JI, Blangiardo M, Toledano MB, et al., 2016, Is long-term exposure to traffic pollution associated with mortality? A small-area study in London, Environmental Pollution, Vol: 208, Pages: 25-32, ISSN: 0269-7491
Halonen JI, Blangiardo M, Toledano MB, et al., 2016, Long-term exposure to traffic pollution and hospital admissions in London, Environmental pollution, Vol: 208, Pages: 48-57, ISSN: 1873-6424
Gulliver J, Morley D, Vienneau D, et al., 2015, Development of an open-source road traffic noise model for exposure assessment, Environmental Modelling & Software, Vol: 74, Pages: 183-193, ISSN: 1364-8152
This paper describes the development of a model for assessing TRAffic Noise EXposure (TRANEX) in anopen-source geographic information system. Instead of using proprietary software we developed ourown model for two main reasons: 1) so that the treatment of source geometry, traffic information (flows/speeds/spatially varying diurnal traffic profiles) and receptors matched as closely as possible to that ofthe air pollution modelling being undertaken in the TRAFFIC project, and 2) to optimize model performancefor practical reasons of needing to implement a noise model with detailed source geometry, overa large geographical area, to produce noise estimates at up to several million address locations, withlimited computing resources. To evaluate TRANEX, noise estimates were compared with noise measurementsmade in the British cities of Leicester and Norwich. High correlation was seen betweenmodelled and measured LAeq,1hr (Norwich: r ¼ 0.85, p ¼ .000; Leicester: r ¼ 0.95, p ¼ .000) with averagemodel errors of 3.1 dB. TRANEX was used to estimate noise exposures (LAeq,1hr, LAeq,16hr, Lnight) for theresident population of London (2003e2010). Results suggest that 1.03 million (12%) people are exposedto daytime road traffic noise levels 65 dB(A) and 1.63 million (19%) people are exposed to night-timeroad traffic noise levels 55 dB(A). Differences in noise levels between 2010 and 2003 were on averagerelatively small: 0.25 dB (standard deviation: 0.89) and 0.26 dB (standard deviation: 0.87) for LAeq,16hrand Lnight.
Halonen JI, Hansell AL, Gulliver J, et al., 2015, Road traffic noise is associated with increased cardiovascular morbidity and mortality and all-cause mortality in London, European Heart Journal, Vol: 36, Pages: 2653-2661, ISSN: 0195-668X
AimsRoad traffic noise has been associated with hypertension but evidence for the long-term effects on hospital admissions and mortality is limited. We examined the effects of long-term exposure to road traffic noise on hospital admissions and mortality in the general population.Methods and resultsThe study population consisted of 8.6 million inhabitants of London, one of Europe's largest cities. We assessed small-area-level associations of day- (7:00–22:59) and nighttime (23:00–06:59) road traffic noise with cardiovascular hospital admissions and all-cause and cardiovascular mortality in all adults (≥25 years) and elderly (≥75 years) through Poisson regression models. We adjusted models for age, sex, area-level socioeconomic deprivation, ethnicity, smoking, air pollution, and neighbourhood spatial structure. Median daytime exposure to road traffic noise was 55.6 dB. Daytime road traffic noise increased the risk of hospital admission for stroke with relative risk (RR) 1.05 [95% confidence interval (CI): 1.02–1.09] in adults, and 1.09 (95% CI: 1.04–1.14) in the elderly in areas >60 vs. <55 dB. Nighttime noise was associated with stroke admissions only among the elderly. Daytime noise was significantly associated with all-cause mortality in adults [RR 1.04 (95% CI: 1.00–1.07) in areas >60 vs. <55 dB]. Positive but non-significant associations were seen with mortality for cardiovascular and ischaemic heart disease, and stroke. Results were similar for the elderly.ConclusionsLong-term exposure to road traffic noise was associated with small increased risks of all-cause mortality and cardiovascular mortality and morbidity in the general population, particularly for stroke in the elderly.
Fecht D, Anderson I, Fabbri F, et al., 2015, Birth Outcomes And Maternal Exposure To Natural Environments In A Metropolitan Area, 27th annual meeting of the International Society for Environmental Epidemiology (ISEE)
Morley DW, de Hoogh K, Fecht D, et al., 2015, International scale implementation of the CNOSSOS-EU road traffic noise prediction model for epidemiological studies, Environmental Pollution, Vol: 206, Pages: 332-341, ISSN: 0269-7491
The EU-FP7-funded BioSHaRE project is using individual-level data pooled from several national cohort studies in Europe to investigate the relationship of road traffic noise and health. The detailed input data (land cover and traffic characteristics) required for noise exposure modelling are not always available over whole countries while data that are comparable in spatial resolution between different countries is needed for harmonised exposure assessment. Here, we assess the feasibility using the CNOSSOS-EU road traffic noise prediction model with coarser input data in terms of model performance. Starting with a model using the highest resolution datasets, we progressively introduced lower resolution data over five further model runs and compared noise level estimates to measurements. We conclude that a low resolution noise model should provide adequate performance for exposure ranking (Spearman's rank = 0.75; p < 0.001), but with relatively large errors in predicted noise levels (RMSE = 4.46 dB(A)).
PLOS ONE Staff, 2015, Correction: Associations between green space and health in English cities: an ecological, cross-sectional study., PLoS One, Vol: 10, Pages: 1-2, ISSN: 1932-6203
Bixby HRH, Hodgson S, Fortunato L, et al., 2015, Associations between Green Space and Health in English Cities: An Ecological, Cross-Sectional Study, PLOS One, Vol: 10, ISSN: 1932-6203
Fecht D, Fischer P, Fortunato L, et al., 2015, Associations between air pollution and socioeconomic characteristics, ethnicity and age profile of neighbourhoods in England and the Netherlands, ENVIRONMENTAL POLLUTION, Vol: 198, Pages: 201-210, ISSN: 0269-7491
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Gulliver J, Morley D, Fecht D, et al., 2015, 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 LAeq1hr from 38 locations in Leicester, a medium sized city in the UK. The lowest resolution model performed reasonably well in terms of correlation [rs = 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.
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