88 results found
Karamanos A, Mudway I, Kelly F, et al., 2021, Air pollution and trajectories of adolescent conduct problems: the roles of ethnicity and racism; evidence from the DASH longitudinal study., Soc Psychiatry Psychiatr Epidemiol
PURPOSE: No known UK empirical research has investigated prospective associations between ambient air pollutants and conduct problems in adolescence. Ethnic minority children are disproportionately exposed to structural factors that could moderate any observed relationships. This prospective study examined whether exposure to PM2.5 and NO2 concentrations is associated with conduct problems in adolescence, and whether racism or ethnicity moderate such associations. METHODS: Longitudinal associations between annual mean estimated PM2.5 and NO2 concentrations at the residential address and trajectories of conduct problems, and the potential influence of racism and ethnicity were examined school-based sample of 4775 participants (2002-2003 to 2005-2006) in London, using growth curve models. RESULTS: Overall, in the fully adjusted model, exposure to lower concentrations of PM2.5 and NO2 was associated with a decrease in conduct problems during adolescence, while exposure to higher concentrations was associated with a flattened trajectory of conduct symptoms. Racism amplified the effect of PM2.5 (β = 0.05 (95% CI 0.01 to 0.10, p < 0.01)) on adolescent trajectories of conduct problems over time. At higher concentrations of PM2.5, there was a divergence of trajectories of adolescent conduct problems between ethnic minority groups, with White British and Black Caribbean adolescents experiencing an increase in conduct problems over time. CONCLUSION: These findings suggest that the intersections between air pollution, ethnicity, and racism are important influences on the development of conduct problems in adolescence.
Reuben A, Arseneault L, Beddows A, et al., 2021, Association of Air Pollution Exposure in Childhood and Adolescence With Psychopathology at the Transition to Adulthood, JAMA NETWORK OPEN, Vol: 4, ISSN: 2574-3805
Latham RM, Kieling C, Arseneault L, et al., 2021, Childhood exposure to ambient air pollution and predicting individual risk of depression onset in UK adolescents., J Psychiatr Res, Vol: 138, Pages: 60-67
Knowledge about early risk factors for major depressive disorder (MDD) is critical to identify those who are at high risk. A multivariable model to predict adolescents' individual risk of future MDD has recently been developed however its performance in a UK sample was far from perfect. Given the potential role of air pollution in the aetiology of depression, we investigate whether including childhood exposure to air pollution as an additional predictor in the risk prediction model improves the identification of UK adolescents who are at greatest risk for developing MDD. We used data from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally representative UK birth cohort of 2232 children followed to age 18 with 93% retention. Annual exposure to four pollutants - nitrogen dioxide (NO2), nitrogen oxides (NOX), particulate matter <2.5 μm (PM2.5) and <10 μm (PM10) - were estimated at address-level when children were aged 10. MDD was assessed via interviews at age 18. The risk of developing MDD was elevated most for participants with the highest (top quartile) level of annual exposure to NOX (adjusted OR = 1.43, 95% CI = 0.96-2.13) and PM2.5 (adjusted OR = 1.35, 95% CI = 0.95-1.92). The separate inclusion of these ambient pollution estimates into the risk prediction model improved model specificity but reduced model sensitivity - resulting in minimal net improvement in model performance. Findings indicate a potential role for childhood ambient air pollution exposure in the development of adolescent MDD but suggest that inclusion of risk factors other than this may be important for improving the performance of the risk prediction model.
Hicks W, Beevers S, Tremper A, et al., 2021, Quantification of non-exhaust particulate matter traffic emissions and the impact of COVID-19 lockdown at London Marylebone Road, Atmosphere, Vol: 12, Pages: 1-19, ISSN: 2073-4433
This research quantifies current sources of non-exhaust particulate matter traffic emissions in London using simultaneous, highly time-resolved, atmospheric particulate matter mass and chemical composition measurements. The measurement campaign ran at Marylebone Road (roadside) and Honor Oak Park (background) urban monitoring sites over a 12-month period between 1 September 2019 and 31 August 2020. The measurement data has been used to determine the traffic increment (roadside – background) and covers a range of meteorological conditions, seasons and driving styles, as well as the influence of the COVID-19 ‘lockdown’ on non-exhaust concentrations. Non-exhaust PM10 concentrations are calculated using chemical tracer scaling factors for brake wear (barium), tyre wear (zinc) and resuspension (silicon) and as average vehicle fleet non-exhaust emission factors, using a CO2 ‘dilution approach’. The effect of lockdown, which saw a 32% reduction in traffic volume and a 15% increase in average speed on Marylebone Road, resulted in lower PM10 and PM2.5 traffic increments and brake wear concentrations, but similar tyre and resuspension concentrations, confirming that factors that determine non-exhaust emissions are complex. Brake wear was found to be the highest average non-exhaust emission source. In addition, results indicated that non-exhaust emission factors are dependent upon speed and road surface wetness conditions. Further statistical analysis incorporating a wider variability in vehicle mix, speeds and meteorological conditions, as well as advanced source apportionment of the PM measurement data, will be undertaken to enhance our understanding of these important vehicle sources.
Bakolis I, Hammoud R, Stewart R, et al., 2020, Mental health consequences of urban air pollution: prospective population-based longitudinal survey, Social Psychiatry and Psychiatric Epidemiology: the international journal for research in social and genetic epidemiology and mental health services, Vol: 2020, Pages: 1-13, ISSN: 0933-7954
PURPOSE: The World Health Organisation (WHO) recently ranked air pollution as the major environmental cause of premature death. However, the significant potential health and societal costs of poor mental health in relation to air quality are not represented in the WHO report due to limited evidence. We aimed to test the hypothesis that long-term exposure to air pollution is associated with poor mental health. METHODS: A prospective longitudinal population-based mental health survey was conducted of 1698 adults living in 1075 households in South East London, from 2008 to 2013. High-resolution quarterly average air pollution concentrations of nitrogen dioxide (NO2) and oxides (NOx), ozone (O3), particulate matter with an aerodynamic diameter < 10 μm (PM10) and < 2.5 μm (PM2.5) were linked to the home addresses of the study participants. Associations with mental health were analysed with the use of multilevel generalised linear models, after adjusting for large number of confounders, including the individuals' socioeconomic position and exposure to road-traffic noise. RESULTS: We found robust evidence for interquartile range increases in PM2.5, NOx and NO2 to be associated with 18-39% increased odds of common mental disorders, 19-30% increased odds of poor physical symptoms and 33% of psychotic experiences only for PM10. These longitudinal associations were more pronounced in the subset of non-movers for NO2 and NOx. CONCLUSIONS: The findings suggest that traffic-related air pollution is adversely affecting mental health. Whilst causation cannot be proved, this work suggests substantial morbidity from mental disorders could be avoided with improved air quality.
Clark S, Alli AS, Brauer M, et al., 2020, High-resolution spatiotemporal measurement of air and environmental noise pollution in sub-Saharan African cities: Pathways to Equitable Health Cities Study protocol for Accra, Ghana, BMJ Open, Vol: 10, ISSN: 2044-6055
Introduction: Air and noise pollution are emerging environmental health hazards in African cities, with potentially complex spatial and temporal patterns. Limited local data is a barrier to the formulation and evaluation of policies to reduce air and noise pollution. Methods and analysis: We designed a year-long measurement campaign to characterize air and noise pollution and their sources at high-resolution within the Greater Accra Metropolitan Area, Ghana. Our design utilizes a combination of fixed (year-long, n = 10) and rotating (week-long, n = ~130) sites, selected to represent a range of land uses and source influences (e.g. background, road-traffic, commercial, industrial, and residential areas, and various neighbourhood socioeconomic classes). We will collect data on fine particulate matter (PM2.5), nitrogen oxides (NOx), weather variables, sound (noise level and audio) along with street-level time-lapse images. We deploy low-cost, low-power, lightweight monitoring devices that are robust, socially unobtrusive, and able to function in the Sub-Saharan African (SSA) climate. We will use state-of-the-art methods, including spatial statistics, deep/machine learning, and processed-based emissions modelling, to capture highly resolved temporal and spatial variations in pollution levels across Accra and to identify their potential sources. This protocol can serve as a prototype for other SSA cities. Ethics and dissemination: This environmental study was deemed exempt from full ethics review at Imperial College London and the University of Massachusetts Amherst; it was approved by the University of Ghana Ethics Committee. This protocol is designed to be implementable in SSA cities to map environmental pollution to inform urban planning decisions to reduce health harming exposures to air and noise pollution. It will be disseminated through local stakeholder engagement (public and private sectors), peer-reviewed publications, contribution to policy documents, media, a
Butland BK, Samoli E, Atkinson RW, et al., 2020, Comparing the performance of air pollution models for nitrogen dioxide and ozone in the context of a multilevel epidemiological analysis., Environ Epidemiol, Vol: 4
Using modeled air pollutant predictions as exposure variables in epidemiological analyses can produce bias in health effect estimation. We used statistical simulation to estimate these biases and compare different air pollution models for London. Methods: Our simulations were based on a sample of 1,000 small geographical areas within London, United Kingdom. "True" pollutant data (daily mean nitrogen dioxide [NO2] and ozone [O3]) were simulated to include spatio-temporal variation and spatial covariance. All-cause mortality and cardiovascular hospital admissions were simulated from "true" pollution data using prespecified effect parameters for short and long-term exposure within a multilevel Poisson model. We compared: land use regression (LUR) models, dispersion models, LUR models including dispersion output as a spline (hybrid1), and generalized additive models combining splines in LUR and dispersion outputs (hybrid2). Validation datasets (model versus fixed-site monitor) were used to define simulation scenarios. Results: For the LUR models, bias estimates ranged from -56% to +7% for short-term exposure and -98% to -68% for long-term exposure and for the dispersion models from -33% to -15% and -52% to +0.5%, respectively. Hybrid1 provided little if any additional benefit, but hybrid2 appeared optimal in terms of bias estimates for short-term (-17% to +11%) and long-term (-28% to +11%) exposure and in preserving coverage probability and statistical power. Conclusions: Although exposure error can produce substantial negative bias (i.e., towards the null), combining outputs from different air pollution modeling approaches may reduce bias in health effect estimation leading to improved impact evaluation of abatement policies.
Samoli E, Butland BK, Rodopoulou S, et al., 2020, The impact of measurement error in modeled ambient particles exposures on health effect estimates in multilevel analysis: A simulation study., Environ Epidemiol, Vol: 4
Various spatiotemporal models have been proposed for predicting ambient particulate exposure for inclusion in epidemiological analyses. We investigated the effect of measurement error in the prediction of particulate matter with diameter <10 µm (PM10) and <2.5 µm (PM2.5) concentrations on the estimation of health effects. Methods: We sampled 1,000 small administrative areas in London, United Kingdom, and simulated the "true" underlying daily exposure surfaces for PM10 and PM2.5 for 2009-2013 incorporating temporal variation and spatial covariance informed by the extensive London monitoring network. We added measurement error assessed by comparing measurements at fixed sites and predictions from spatiotemporal land-use regression (LUR) models; dispersion models; models using satellite data and applying machine learning algorithms; and combinations of these methods through generalized additive models. Two health outcomes were simulated to assess whether the bias varies with the effect size. We applied multilevel Poisson regression to simultaneously model the effect of long- and short-term pollutant exposure. For each scenario, we ran 1,000 simulations to assess measurement error impact on health effect estimation. Results: For long-term exposure to particles, we observed bias toward the null, except for traffic PM2.5 for which only LUR underestimated the effect. For short-term exposure, results were variable between exposure models and bias ranged from -11% (underestimate) to 20% (overestimate) for PM10 and of -20% to 17% for PM2.5. Integration of models performed best in almost all cases. Conclusions: No single exposure model performed optimally across scenarios. In most cases, measurement error resulted in attenuation of the effect estimate.
Desouza CD, Marsh DJ, Beevers SD, et al., 2020, Real-world emissions from non-road mobile machinery in London, Atmospheric Environment, Vol: 223, ISSN: 1352-2310
The 2016 London atmospheric emissions inventory estimates that, the construction sector contributes 34% of the total PM and 7% of the total NO – the largest and 5 largest sources, respectively. Recent on-road light duty diesel vehicle emission tests have shown significant differences between real-world NO emissions compared with results from laboratory based regulatory tests. The aim of this study was therefore to quantify the ‘real-world’ tail-pipe NO , CO , and particle emissions, for 30 of the most commonly used construction machines in London under normal working conditions. The highest NO emissions (g/kWh) were from the older engines (Stage III-A ~4.88 g/kWh and III-B ~4.61 g/kWh), these were reduced significantly (~78%) in the newer (Stage IV ~1.05 g/kWh) engines due to more advanced engine management systems and exhaust after treatment. One Stage IV machine emitted NO similar to a Stage III-B machine, the failure of this SCR was only detectable using PEMS as no warning was given by the machine. Higher NO conformity factors were observed for Stage IV machines, due to the lower NO emission standards, which these machines must adhere to. On average, Stage III-B machines (~525 g/kWh) emitted the lowest levels of CO emissions, compared to Stage III-A (~875 g/kWh) and Stage IV (~575 g/kWh) machines. Overall, a statistically significant (~41%) decrease was observed in the CO emissions (g/kWh) between Stage III-A and III-B machines, while no statistically significant difference was found between Stage III-B and IV machines. Particle mass measurements, which were only measured from generators, showed that generators of all engine sizes were within their respective Stage III-A emission standards. A 95% reduction in NO and 2 orders of magnitude reduction in particle number was observed for a SCR-DPF retrofitted generator, compared to the same generator prior to exhaust gas after-treatment strategy. 10 X X X 2 X X X X 2 2 X th
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.
Petit C, Wentz E, Randolph B, et al., 2019, Tackling the challenge of growing cities: An informed urbanisation approach, Open Cities | Open Data: Collaborative Cities in the Information Era, Pages: 197-219, ISBN: 9789811366048
Two global transformative changes-rapid urbanisation and mass digital disruption-are brought together in the concept of ‘Informed Urbanisation’. This approach stands in contrast with the more common and more problematic ‘accidental urbanisation’ that is unsustainable, responsive urban growth driven by population demand and economic development. Informed urbanisation offers the means to decipher cities, comprising integral systems of networks and flows, through rigorous and comprehensive analysis of the multitude of data on housing, transport, city resilience, city migration and other aspects of urban change. In this chapter we introduce an Informed Urbanisation framework and present case studies on how it is being designed and activated in the cities of Phoenix, London and Sydney.
Mudway IS, Dundas I, Wood HE, et al., 2019, Impact of London's low emission zone on air quality and children's respiratory health, The Lancet Public Health, Vol: 4, Pages: e28-e40, ISSN: 2468-2667
BACKGROUND: Low emission zones (LEZ) are an increasingly common, but unevaluated, intervention aimed at improving urban air quality and public health. We investigated the impact of London's LEZ on air quality and children's respiratory health.METHODS: We did a sequential annual cross-sectional study of 2164 children aged 8-9 years attending primary schools between 2009-10 and 2013-14 in central London, UK, following the introduction of London's LEZ in February, 2008. We examined the association between modelled pollutant exposures of nitrogen oxides (including nitrogen dioxide [NO2]) and particulate matter with a diameter of less than 2·5 μm (PM2·5) and less than 10 μm (PM10) and lung function: postbronchodilator forced expiratory volume in 1 s (FEV1, primary outcome), forced vital capacity (FVC), and respiratory or allergic symptoms. We assigned annual exposures by each child's home and school address, as well as spatially resolved estimates for the 3 h (0600-0900 h), 24 h, and 7 days before each child's assessment, to isolate long-term from short-term effects.FINDINGS: The percentage of children living at addresses exceeding the EU limit value for annual NO2 (40 μg/m3) fell from 99% (444/450) in 2009 to 34% (150/441) in 2013. Over this period, we identified a reduction in NO2 at both roadside (median -1·35 μg/m3 per year; 95% CI -2·09 to -0·61; p=0·0004) and background locations (-0·97; -1·56 to -0·38; p=0·0013), but not for PM10. The effect on PM2·5 was equivocal. We found no association between postbronchodilator FEV1 and annual residential pollutant attributions. By contrast, FVC was inversely correlated with annual NO2 (-0·0023 L/μg per m3; -0·0044 to -0·0002; p=0·033) and PM10 (-0·0090 L/μg per m3; -0·0175 to -0·0005; p=0·038).INTERPRETATION: Within London's LEZ, a smaller lung volume in children was associated
, 2019, Exploration of NO2 and PM2.5 air pollution and mental health problems using high-resolution data in London-based children from a UK longitudinal cohort study, Vol: 272, Pages: 8-17, ISSN: 1872-7123
Newbury JB, Arseneault L, Beevers S, et al., 2019, Association of Air Pollution Exposure With Psychotic Experiences During Adolescence, JAMA Psychiatry, Vol: 76, Pages: 614-623, ISSN: 2168-622X
Importance Urbanicity is a well-established risk factor for clinical (eg, schizophrenia) and subclinical (eg, hearing voices and paranoia) expressions of psychosis. To our knowledge, no studies have examined the association of air pollution with adolescent psychotic experiences, despite air pollution being a major environmental problem in cities.Objectives To examine the association between exposure to air pollution and adolescent psychotic experiences and test whether exposure mediates the association between urban residency and adolescent psychotic experiences.Design, Setting, and Participants The Environmental-Risk Longitudinal Twin Study is a population-based cohort study of 2232 children born during the period from January 1, 1994, through December 4, 1995, in England and Wales and followed up from birth through 18 years of age. The cohort represents the geographic and socioeconomic composition of UK households. Of the original cohort, 2066 (92.6%) participated in assessments at 18 years of age, of whom 2063 (99.9%) provided data on psychotic experiences. Generation of the pollution data was completed on October 4, 2017, and data were analyzed from May 4 to November 21, 2018.Exposures High-resolution annualized estimates of exposure to 4 air pollutants—nitrogen dioxide (NO2), nitrogen oxides (NOx), and particulate matter with aerodynamic diameters of less than 2.5 (PM2.5) and less than 10 μm (PM10)—were modeled for 2012 and linked to the home addresses of the sample plus 2 commonly visited locations when the participants were 18 years old.Main Outcomes and Measures At 18 years of age, participants were privately interviewed regarding adolescent psychotic experiences. Urbanicity was estimated using 2011 census data.Results Among the 2063 participants who provided data on psychotic experiences, sex was evenly distributed (52.5% female). Six hundred twenty-three participants (30.2%) had at least 1 psychotic experience from 12 to 18 years of ag
Carey IM, Anderson HR, Atkinson RW, et al., 2018, Are noise and air pollution related to the incidence of dementia? A cohort study in London, England, BMJ Open, Vol: 8, ISSN: 2044-6055
OBJECTIVE: To investigate whether the incidence of dementia is related to residential levels of air and noise pollution in London. DESIGN: Retrospective cohort study using primary care data. SETTING: 75 Greater London practices. PARTICIPANTS: 130 978 adults aged 50-79 years registered with their general practices on 1 January 2005, with no recorded history of dementia or care home residence. PRIMARY AND SECONDARY OUTCOME MEASURES: A first recorded diagnosis of dementia and, where specified, subgroups of Alzheimer's disease and vascular dementia during 2005-2013. The average annual concentrations during 2004 of nitrogen dioxide (NO2), particulate matter with a median aerodynamic diameter </=2.5 microm (PM2.5) and ozone (O3) were estimated at 20x20 m resolution from dispersion models. Traffic intensity, distance from major road and night-time noise levels (Lnight) were estimated at the postcode level. All exposure measures were linked anonymously to clinical data via residential postcode. HRs from Cox models were adjusted for age, sex, ethnicity, smoking and body mass index, with further adjustments explored for area deprivation and comorbidity. RESULTS: 2181 subjects (1.7%) received an incident diagnosis of dementia (39% mentioning Alzheimer's disease, 29% vascular dementia). There was a positive exposure response relationship between dementia and all measures of air pollution except O3, which was not readily explained by further adjustment. Adults living in areas with the highest fifth of NO2 concentration (>41.5 microg/m(3)) versus the lowest fifth (<31.9 microg/m(3)) were at a higher risk of dementia (HR=1.40, 95% CI 1.12 to 1.74). Increases in dementia risk were also observed with PM2.5, PM2.5 specifically from primary traffic sources only and Lnight, but only NO2 and PM2.5 remained statistically significant in multipollutant models. Associations were more consistent for Alzheimer's disease than vascular dementia. CONCLUSIONS: We have found evidence of a
Moore E, Lewis A, hashmi M, et al., 2018, Recruitment of patients with Chronic Obstructive Pulmonary Disease (COPD) from the Clinical Practice Research Datalink (CPRD) for research, npj Primary Care Respiratory Medicine, Vol: 28, ISSN: 2055-1010
Databases of electronic health records (EHR) are not only a valuable source of data for health research but have also recently been used as a medium through which potential study participants can be screened, located and approached to take part in research. The aim was to assess whether it is feasible and practical to screen, locate and approach patients to take part in research through the Clinical Practice Research Datalink (CPRD). This is a cohort study in primary care. The CPRD anonymised EHR database was searched to screen patients with Chronic Obstructive Pulmonary Disease (COPD) to take part in a research study. The potential participants were contacted via their General Practitioner (GP) who confirmed their eligibility. Eighty two practices across Greater London were invited to the study. Twenty-six (31.7%) practices consented to participate resulting in a pre-screened list of 988 patients. Of these, 632 (63.7%) were confirmed as eligible following the GP review. Two hundred twenty seven (36%) response forms were received by the study team; 79 (34.8%) responded ‘yes’ (i.e., they wanted to be contacted by the research assistant for more information and to talk about enrolling in the study), and 148 (65.2%) declined participation. This study has shown that it is possible to use EHR databases such as CPRD to screen, locate and recruit participants for research. This method provides access to a cohort of patients while minimising input needed by GPs and allows researchers to examine healthcare usage and disease burden in more detail and in real-life settings.
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
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
Barratt B, Chatzidiakou L, Moore E, et al., 2017, Characterisation of COPD exacerbations using personal environmental exposure monitoring, European-Respiratory-Society (ERS) International Congress, Publisher: EUROPEAN RESPIRATORY SOC JOURNALS LTD, ISSN: 0903-1936
Butland BK, Atkinson RW, Crichton S, et al., 2017, Air pollution and the incidence of ischaemic and haemorrhagic stroke in the South London Stroke Register: a case-cross-over analysis, Journal of Epidemiology and Community Health, Vol: 71, Pages: 707-712, ISSN: 0143-005X
Dajnak D, Stewart G, Beevers S, 2017, Policies for london nitrogen dioxide (NO<inf>2</inf>)compliance, Pages: 218-222
Over one tenth of the UK population live in London and since London’s air pollution concentrations are predicted to exceed legal NO limits until at least 2030 (DEFRA, 2015), London requires a bold combination of policies to tackle its air pollution problems. Road transport is the most significant source of NO emissions in London with diesel vehicles the greatest contributor (TfL and GLA, 2013/2016). The current air pollution challenge, primarily caused by a shift from petrol to diesel vehicles over the last 15 years, needs to be recognised and reversed. Our study in partnership with Policy Exchange (PX), the Institute for Public Policy Research (IPPR) and Greenpeace (GP) builds on the Greater London Authority (GLA) implementation of the Ultra Low Emission Zone (ULEZ) in 2020 (TfL, 2014). Our ambitious air quality strategy proposes a comprehensive package of measures focusing on road transport policies such as phasing out diesel cars in inner London, moving toward more sustainable road transport alternatives, restricting the most polluting vehicles entering London, cleaning up taxi and bus fleets, promoting electric vehicles and car clubs. The proposed policies (the scenario) result in large reductions in NO emissions (45%) across London, relative to the projected outcome of the ULEZ (TfL, 2014) from the previous administration (the baseline). Our modelling results suggest significant improvement bringing nearly the whole of London into compliance with legal NO limits by 2025 and decreasing NO concentration levels below 20 μgm from 16% in the baseline to nearly 36% in the scenario. This is important since there are still health impacts below the 40 μgm limit value. However, some key hotspots of pollution, on major roads, still remain non-compliant and will need additional localised targeted actions. These air quality improvements are projected to have a pronounced positive effect upon health outcomes in the capital. Life expectancy for all Londoner
Beddows AV, Kitwiroon N, Williams ML, et al., 2017, Emulation and Sensitivity Analysis of the Community Multiscale Air Quality Model for a UK Ozone Pollution Episode, Environmental science & technology, Vol: 51, Pages: 6229-6236, ISSN: 0013-936X
Gaussian process emulation techniques have been used with the Community Multiscale Air Quality model, simulating the effects of input uncertainties on ozone and NO2 output, to allow robust global sensitivity analysis (SA). A screening process ranked the effect of perturbations in 223 inputs, isolating the 30 most influential from emissions, boundary conditions (BCs), and reaction rates. Community Multiscale Air Quality (CMAQ) simulations of a July 2006 ozone pollution episode in the UK were made with input values for these variables plus ozone dry deposition velocity chosen according to a 576 point Latin hypercube design. Emulators trained on the output of these runs were used in variance-based SA of the model output to input uncertainties. Performing these analyses for every hour of a 21 day period spanning the episode and several days on either side allowed the results to be presented as a time series of sensitivity coefficients, showing how the influence of different input uncertainties changed during the episode. This is one of the most complex models to which these methods have been applied, and here, they reveal detailed spatiotemporal patterns of model sensitivities, with NO and isoprene emissions, NO2 photolysis, ozone BCs, and deposition velocity being among the most influential input uncertainties.
Bino M, Lefebvre W, Walton H, et al., 2017, Sensitivity analyses regarding NO2 exposure assessment and health impacts at a European scale, 18th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes
Currently, no adequate methodology exists to assess the NO2 health impacts at an EU-wide level. To a large extent this is attributed to the level of detail required in the NO2 concentration assessment at EU-level due to the strong spatial gradients for NO2 around roads. In this contribution we present a sensitivity analysis of the major sources of uncertainty in such an EU-wide health impact assessment for NO2. We do this by means of a number of bottom-up NO2 assessment maps contributed through the FAIRMODE composite mapping platform. We investigate the impact of the spatial resolution of the NO2 assessment, the available dose response curves and a number of ancillary datasets such as gridded population. We find that the largest source of uncertainty is found in the divergence between the different CRF’s available, in particular the choice of a ‘cut-off’ or ‘threshold’. For some cities, such as London, the difference is relatively small. However, the difference for smaller cities, such as Klagenfurt can go up to a factor of 6. Spatial resolution of the air quality maps and population maps is an important factor and depending on the concentration response function, the sensitivity is stronger. This work has been performed in the framework of the DG-ENV service contract 070201/2015/SER/717473/C.3, the conclusions of which contributed to the development of an EU-wide high resolution NO2 exposure assessment methodology.
Moore E, Hashmi M, Sultana K, et al., 2016, Using the Clinical Practice Research Datalink (CPRD) to recruit participants from primary care to investigate Chronic Obstructive Pulmonary Disease (COPD) exacerbations., British Thoracic Society Winter Meeting 2016
Moore EA, Chatzidiakou L, Kuku M-O, et al., 2016, Global associations between air pollutants and Chronic Obstructive Pulmonary Disease (COPD) exacerbations: a systematic review, European Respiratory Society Congress 2016, Publisher: European Respiratory Society, Pages: PA1126-PA1126, ISSN: 0903-1936
Background: COPD exacerbations (AECOPD) affect lung function decline and quality of life. The effect of exposure to different air pollutants on AECOPD is unclear.Aim: We systematically reviewed the literature examining associations between air pollutants and hospital admissions for AECOPD.Methods: MEDLINE, EMBASE, BIOSIS & Science Citation Index were searched until September 2015. Inclusion criteria focused on studies presenting solely a COPD outcome defined by hospital admissions, and a measure of gaseous air pollutants and particle fractions. The association between each pollutant with COPD admissions was investigated in meta-analyses using random-effects models. Analyses were stratified by geographical clusters to investigate the evidence worldwide.Results: 46 studies were included and results showed marginal positive associations. The number of included studies was small with high heterogeneity between them and there was evidence of small-study bias. Geographical clustering of the effects of pollution on COPD hospital admissions was evident and reduced heterogeneity significantly. The most consistent association was between a 1mg/m3 increase in carbon monoxide levels with COPD related admissions; Odds Ratio: 1.2 (95%CI: 1.01-1.03).Conclusions: There is mixed evidence on the effects of pollution on AECOPD. Limitations of previous studies include the low spatio-temporal resolution of pollutants, inadequate control for confounding factors, and the use of aggregated health data that ignore personal characteristics. The need for personal exposure monitoring in a large number of geographical locations is evident.
Desika A, Crichton S, Hoang U, et al., 2016, Effect of exhaust- and nonexhaust-related components of particulate matter on long-term survival after stroke, Stroke, Vol: 47, Pages: 2916-2922, ISSN: 0039-2499
Smith JD, Mitsakou C, Kitwiroon N, et al., 2016, London hybrid exposure model: improving human exposure estimates to NO2 and PM2.5 in an urban setting, Environmental Science and Technology (Washington), Vol: 50, Pages: 11760-11768, ISSN: 0013-936X
Here we describe the development of the London Hybrid Exposure Model (LHEM), which calculates exposure of the Greater London population to outdoor air pollution sources, in-buildings, in-vehicles and outdoors, using survey data of when and where people spend their time. For comparison and to estimate exposure misclassification we compared Londoners LHEM exposure with exposure at the residential address, a commonly used exposure metric in epidemiological research. In 2011, the mean annual LHEM exposure to outdoor sources was estimated to be 37÷ lower for PM2.5 and 63÷ lower for NO2 than at the residential address. These decreased estimates reflect, the effects of reduced exposure indoors, the amount of time spent indoors (95÷), and the mode and duration of travel in London. We find that an individual's exposure to PM2.5 and NO2 outside their residential address is highly correlated (Pearson's R of 0.9). In contrast, LHEM exposure estimates for PM2.5 and NO2 suggest that the degree of correlation is influe...
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.