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Prof. David Briggs
Emeritus Professor, Department of Epidemiology & Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK

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0 Air Pollution
0 Exposure Assessment
0 GIS
0 Environmental health indicators
0 Environmental health impact assessment

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Environmental health impact assessment

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Journal article
Published: 22 December 2015 in International Journal of Environmental Research and Public Health
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An integrated environmental health impact assessment of road transport in New Zealand was carried out, using a rapid assessment. The disease and injury burden was assessed from traffic-related accidents, air pollution, noise and physical (in)activity, and impacts attributed back to modal source. In total, road transport was found to be responsible for 650 deaths in 2012 (2.1% of annual mortality): 308 from traffic accidents, 283 as a result of air pollution, and 59 from noise. Together with morbidity, these represent a total burden of disease of 26,610 disability-adjusted life years (DALYs). An estimated 40 deaths and 1874 DALYs were avoided through active transport. Cars are responsible for about 52% of attributable deaths, but heavy goods vehicles (6% of vehicle kilometres travelled, vkt) accounted for 21% of deaths. Motorcycles (1 per cent of vkt) are implicated in nearly 8% of deaths. Overall, impacts of traffic-related air pollution and noise are low compared to other developed countries, but road accident rates are high. Results highlight the need for policies targeted at road accidents, and especially at heavy goods vehicles and motorcycles, along with more general action to reduce the reliance on private road transport. The study also provides a framework for national indicator development.

ACS Style

David Briggs; Kylie Mason; Barry Borman. Rapid Assessment of Environmental Health Impacts for Policy Support: The Example of Road Transport in New Zealand. International Journal of Environmental Research and Public Health 2015, 13, 61 .

AMA Style

David Briggs, Kylie Mason, Barry Borman. Rapid Assessment of Environmental Health Impacts for Policy Support: The Example of Road Transport in New Zealand. International Journal of Environmental Research and Public Health. 2015; 13 (1):61.

Chicago/Turabian Style

David Briggs; Kylie Mason; Barry Borman. 2015. "Rapid Assessment of Environmental Health Impacts for Policy Support: The Example of Road Transport in New Zealand." International Journal of Environmental Research and Public Health 13, no. 1: 61.

Book chapter
Published: 01 June 2015 in Exposure Assessment in Environmental Epidemiology
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ACS Style

Kees De Hoogh; John Gulliver; David Briggs; Mark J. Nieuwenhuijsen. Environmental Measurement and Modeling. Exposure Assessment in Environmental Epidemiology 2015, 69 -86.

AMA Style

Kees De Hoogh, John Gulliver, David Briggs, Mark J. Nieuwenhuijsen. Environmental Measurement and Modeling. Exposure Assessment in Environmental Epidemiology. 2015; ():69-86.

Chicago/Turabian Style

Kees De Hoogh; John Gulliver; David Briggs; Mark J. Nieuwenhuijsen. 2015. "Environmental Measurement and Modeling." Exposure Assessment in Environmental Epidemiology , no. : 69-86.

Book chapter
Published: 01 June 2015 in Exposure Assessment in Environmental Epidemiology
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ACS Style

John Gulliver; Kees De Hoogh; David Briggs; Mark J. Nieuwenhuijsen. Environmental Measurement and Modeling. Exposure Assessment in Environmental Epidemiology 2015, 45 -68.

AMA Style

John Gulliver, Kees De Hoogh, David Briggs, Mark J. Nieuwenhuijsen. Environmental Measurement and Modeling. Exposure Assessment in Environmental Epidemiology. 2015; ():45-68.

Chicago/Turabian Style

John Gulliver; Kees De Hoogh; David Briggs; Mark J. Nieuwenhuijsen. 2015. "Environmental Measurement and Modeling." Exposure Assessment in Environmental Epidemiology , no. : 45-68.

Journal article
Published: 06 December 2013 in Emerging Themes in Epidemiology
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Effective interventions require evidence on how individual causal pathways jointly determine disease. Based on the concept of systems epidemiology, this paper develops Diagram-based Analysis of Causal Systems (DACS) as an approach to analyze complex systems, and applies it by examining the contributions of proximal and distal determinants of childhood acute lower respiratory infections (ALRI) in sub-Saharan Africa.

ACS Style

Eva A Rehfuess; Nicky Best; David J Briggs; Mike Joffe. Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa. Emerging Themes in Epidemiology 2013, 10, 13 -13.

AMA Style

Eva A Rehfuess, Nicky Best, David J Briggs, Mike Joffe. Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa. Emerging Themes in Epidemiology. 2013; 10 (1):13-13.

Chicago/Turabian Style

Eva A Rehfuess; Nicky Best; David J Briggs; Mike Joffe. 2013. "Diagram-based Analysis of Causal Systems (DACS): elucidating inter-relationships between determinants of acute lower respiratory infections among children in sub-Saharan Africa." Emerging Themes in Epidemiology 10, no. 1: 13-13.

Cancer
Published: 01 March 2013 in Epidemiology
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Background: Extremely low-frequency magnetic fields are designated as possibly carcinogenic in humans, based on an epidemiologic association with childhood leukemia. Evidence for associations with adult cancers is weaker and inconsistent. Methods: We conducted a case-control study to investigate risks of adult cancers in relation to distance and extremely low-frequency magnetic fields from high-voltage overhead power lines using National Cancer Registry Data in England and Wales, 1974–2008. The study included 7823 leukemia, 6781 brain/central nervous system cancers, 9153 malignant melanoma, 29,202 female breast cancer cases, and 79,507 controls frequency-matched on year and region (three controls per case except for female breast cancer, one control per case) 15–74 years of age living within 1000 m of a high-voltage overhead power line. Results: There were no clear patterns of excess risk with distance from power lines. After adjustment for confounders (age, sex [except breast cancer], deprivation, rurality), for distances closest to the power lines (0–49 m) compared with distances 600–1000 m, odds ratios (ORs) ranged from 0.82 (95% confidence interval = 0.61–1.11; 66 cases) for malignant melanoma to 1.22 (0.88–1.69) for brain/central nervous system cancer. We observed no meaningful excess risks and no trends of risk with magnetic field strength for the four cancers examined. In adjusted analyses at the highest estimated field strength, ≥1000 nanotesla (nT), compared with <100 nT, ORs ranged from 0.68 (0.39–1.17) for malignant melanoma to 1.08 (0.77–1.51) for female breast cancer. Conclusion: Our results do not support an epidemiologic association of adult cancers with residential magnetic fields in proximity to high-voltage overhead power lines.

ACS Style

Paul Elliott; Gavin Shaddick; Margaret Douglass; Kees de Hoogh; David J. Briggs; Mireille B. Toledano. Adult Cancers Near High-voltage Overhead Power Lines. Epidemiology 2013, 24, 184 -190.

AMA Style

Paul Elliott, Gavin Shaddick, Margaret Douglass, Kees de Hoogh, David J. Briggs, Mireille B. Toledano. Adult Cancers Near High-voltage Overhead Power Lines. Epidemiology. 2013; 24 (2):184-190.

Chicago/Turabian Style

Paul Elliott; Gavin Shaddick; Margaret Douglass; Kees de Hoogh; David J. Briggs; Mireille B. Toledano. 2013. "Adult Cancers Near High-voltage Overhead Power Lines." Epidemiology 24, no. 2: 184-190.

Article
Published: 01 September 2012 in Epidemiology
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ACS Style

Fatima Al-Aidarous; Danielle Vienneau; David J. Briggs. O-140. Epidemiology 2012, 23, 1 .

AMA Style

Fatima Al-Aidarous, Danielle Vienneau, David J. Briggs. O-140. Epidemiology. 2012; 23 ():1.

Chicago/Turabian Style

Fatima Al-Aidarous; Danielle Vienneau; David J. Briggs. 2012. "O-140." Epidemiology 23, no. : 1.

Article
Published: 01 September 2012 in Epidemiology
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ACS Style

Zaina Al Kanaani; Rebecca Hardy; Kees De Hoogh; John Gulliver; Chloe Morris; Danielle Vienneau; Kayoung Lee; David Briggs; Diana Kuh; Anna Hansell. P-261. Epidemiology 2012, 23, 1 .

AMA Style

Zaina Al Kanaani, Rebecca Hardy, Kees De Hoogh, John Gulliver, Chloe Morris, Danielle Vienneau, Kayoung Lee, David Briggs, Diana Kuh, Anna Hansell. P-261. Epidemiology. 2012; 23 ():1.

Chicago/Turabian Style

Zaina Al Kanaani; Rebecca Hardy; Kees De Hoogh; John Gulliver; Chloe Morris; Danielle Vienneau; Kayoung Lee; David Briggs; Diana Kuh; Anna Hansell. 2012. "P-261." Epidemiology 23, no. : 1.

Journal article
Published: 01 June 2012 in Science of The Total Environment
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Public concern about possible health effects of EMF radiation from mobile phone masts has led to an increase of epidemiological studies and health risk assessments which, in turn, require adequate methods of exposure estimation. Difficulties in exposure modelling are exacerbated both by the complexity of the propagation processes, and the need to obtain estimates for large study populations in order to provide sufficient statistical power to detect or exclude the small relative risks that might exist. Use of geographical information system (GIS) techniques offers the means to make such computations efficiently. This paper describes the development and field validation of a GIS-based exposure model (Geomorf). The model uses a modified Gaussian formulation to represent spatial variations in power densities around mobile phone masts, on the basis of power output, antenna height, tilt and the surrounding propagation environment. Obstruction by topography is allowed for, through use of a visibility function. Model calibration was done using field data from 151 measurement sites (1510 antenna-specific measurements) around a group of masts in a rural location, and 50 measurement sites (658 antenna-specific measurements) in an urban area. Different parameter settings were found to be necessary in urban and rural areas to obtain optimum results. The calibrated models were then validated against independent sets of data gathered from measurement surveys in rural and urban areas, and model performance was compared with that of two commonly used path-loss models (the COST-231 adaptations of the Hata and Walfisch-Ikegami models). Model performance was found to vary somewhat between the rural and urban areas, and at different measurement levels (antenna-specific power density, total power density), but overall gave good estimates (R(2)=0.641 and 0.615, RMSE=10.7 and 6.7 dB m at the antenna and site-level respectively). Performance was considerably better than that of both path loss models.

ACS Style

David Briggs; Linda Beale; James Bennett; Mireille B. Toledano; Kees De Hoogh. A geographical model of radio-frequency power density around mobile phone masts. Science of The Total Environment 2012, 426, 233 -243.

AMA Style

David Briggs, Linda Beale, James Bennett, Mireille B. Toledano, Kees De Hoogh. A geographical model of radio-frequency power density around mobile phone masts. Science of The Total Environment. 2012; 426 ():233-243.

Chicago/Turabian Style

David Briggs; Linda Beale; James Bennett; Mireille B. Toledano; Kees De Hoogh. 2012. "A geographical model of radio-frequency power density around mobile phone masts." Science of The Total Environment 426, no. : 233-243.

Journal article
Published: 02 June 2011 in Environmental Health
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Policies on waste disposal in Europe are heterogeneous and rapidly changing, with potential health implications that are largely unknown. We conducted a health impact assessment of landfilling and incineration in three European countries: Italy, Slovakia and England. A total of 49 (Italy), 2 (Slovakia), and 11 (England) incinerators were operating in 2001 while for landfills the figures were 619, 121 and 232, respectively. The study population consisted of residents living within 3 km of an incinerator and 2 km of a landfill. Excess risk estimates from epidemiological studies were used, combined with air pollution dispersion modelling for particulate matter (PM10) and nitrogen dioxide (NO2). For incinerators, we estimated attributable cancer incidence and years of life lost (YoLL), while for landfills we estimated attributable cases of congenital anomalies and low birth weight infants. About 1,000,000, 16,000, and 1,200,000 subjects lived close to incinerators in Italy, Slovakia and England, respectively. The additional contribution to NO2 levels within a 3 km radius was 0.23, 0.15, and 0.14 μg/m3, respectively. Lower values were found for PM10. Assuming that the incinerators continue to operate until 2020, we are moderately confident that the annual number of cancer cases due to exposure in 2001-2020 will reach 11, 0, and 7 in 2020 and then decline to 0 in the three countries in 2050. We are moderately confident that by 2050, the attributable impact on the 2001 cohort of residents will be 3,621 (Italy), 37 (Slovakia) and 3,966 (England) YoLL. The total exposed population to landfills was 1,350,000, 329,000, and 1,425,000 subjects, respectively. We are moderately confident that the annual additional cases of congenital anomalies up to 2030 will be approximately 2, 2, and 3 whereas there will be 42, 13, and 59 additional low-birth weight newborns, respectively. The current health impacts of landfilling and incineration can be characterized as moderate when compared to other sources of environmental pollution, e.g. traffic or industrial emissions, that have an impact on public health. There are several uncertainties and critical assumptions in the assessment model, but it provides insight into the relative health impact attributable to waste management.

ACS Style

Francesco Forastiere; Chiara Badaloni; Kees De Hoogh; Martin K Von Kraus; Marco Martuzzi; Francesco Mitis; Lubica Palkovicova; Daniela Porta; Philipp Preiss; Andrea Ranzi; Carlo A Perucci; David Briggs. Health impact assessment of waste management facilities in three European countries. Environmental Health 2011, 10, 53 -53.

AMA Style

Francesco Forastiere, Chiara Badaloni, Kees De Hoogh, Martin K Von Kraus, Marco Martuzzi, Francesco Mitis, Lubica Palkovicova, Daniela Porta, Philipp Preiss, Andrea Ranzi, Carlo A Perucci, David Briggs. Health impact assessment of waste management facilities in three European countries. Environmental Health. 2011; 10 (1):53-53.

Chicago/Turabian Style

Francesco Forastiere; Chiara Badaloni; Kees De Hoogh; Martin K Von Kraus; Marco Martuzzi; Francesco Mitis; Lubica Palkovicova; Daniela Porta; Philipp Preiss; Andrea Ranzi; Carlo A Perucci; David Briggs. 2011. "Health impact assessment of waste management facilities in three European countries." Environmental Health 10, no. 1: 53-53.

Journal article
Published: 15 May 2011 in Science of The Total Environment
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Current methods of air pollution modelling do not readily meet the needs of air pollution mapping for short-term (i.e. daily) exposure studies. The main limiting factor is that for those few models that couple with a GIS there are insufficient tools for directly mapping air pollution both at high spatial resolution and over large areas (e.g. city wide). A simple GIS-based air pollution model (STEMS-Air) has been developed for PM10 to meet these needs with the option to choose different exposure averaging periods (e.g. daily and annual). STEMS-Air uses the grid-based FOCALSUM function in ArcGIS in conjunction with a fine grid of emission sources and basic information on meteorology to implement a simple Gaussian plume model of air pollution dispersion. STEMS-Air was developed and validated in London, UK, using data on concentrations of PM10 from routinely available monitoring data. Results from the validation study show that STEMS-Air performs well in predicting both daily (at four sites) and annual (at 30 sites) concentrations of PM10. For daily modelling, STEMS-Air achieved r2 values in the range 0.19–0.43 (p < 0.001) based solely on traffic-related emissions and r2 values in the range 0.41–0.63 (p < 0.001) when adding information on ‘background’ levels of PM10. For annual modelling of PM10, the model returned r2 in the range 0.67–0.77 (P < 0.001) when compared with monitored concentrations. The model can thus be used for rapid production of daily or annual city-wide air pollution maps either as a screening process in urban air quality planning and management, or as the basis for health risk assessment and epidemiological studies.

ACS Style

John Gulliver; David Briggs. STEMS-Air: A simple GIS-based air pollution dispersion model for city-wide exposure assessment. Science of The Total Environment 2011, 409, 2419 -2429.

AMA Style

John Gulliver, David Briggs. STEMS-Air: A simple GIS-based air pollution dispersion model for city-wide exposure assessment. Science of The Total Environment. 2011; 409 (12):2419-2429.

Chicago/Turabian Style

John Gulliver; David Briggs. 2011. "STEMS-Air: A simple GIS-based air pollution dispersion model for city-wide exposure assessment." Science of The Total Environment 409, no. 12: 2419-2429.

Journal article
Published: 01 November 2009 in Epidemiology
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ACS Style

Danielle Vienneau; Kees de Hoogh; Rob Beelen; Paul Fisher; David Briggs; Gerard Hoek. Investigating the Transferability of Land Use Regression Models Between Two Countries – GB and the Netherlands. Epidemiology 2009, 20, S176 .

AMA Style

Danielle Vienneau, Kees de Hoogh, Rob Beelen, Paul Fisher, David Briggs, Gerard Hoek. Investigating the Transferability of Land Use Regression Models Between Two Countries – GB and the Netherlands. Epidemiology. 2009; 20 ():S176.

Chicago/Turabian Style

Danielle Vienneau; Kees de Hoogh; Rob Beelen; Paul Fisher; David Briggs; Gerard Hoek. 2009. "Investigating the Transferability of Land Use Regression Models Between Two Countries – GB and the Netherlands." Epidemiology 20, no. : S176.

Abstracts
Published: 01 November 2009 in Epidemiology
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ACS Style

Danielle Vienneau; David Briggs. Using GIS to Model Pesticide Exposure at the Small-Area Level in England. Epidemiology 2009, 20, S201 .

AMA Style

Danielle Vienneau, David Briggs. Using GIS to Model Pesticide Exposure at the Small-Area Level in England. Epidemiology. 2009; 20 ():S201.

Chicago/Turabian Style

Danielle Vienneau; David Briggs. 2009. "Using GIS to Model Pesticide Exposure at the Small-Area Level in England." Epidemiology 20, no. : S201.

Abstracts
Published: 01 November 2009 in Epidemiology
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ACS Style

Danielle Vienneau; Kees De Hoogh; David Briggs. A Novel GIS Method for Modelling 1 km NO2 Concentrations across Europe. Epidemiology 2009, 20, S64 -S65.

AMA Style

Danielle Vienneau, Kees De Hoogh, David Briggs. A Novel GIS Method for Modelling 1 km NO2 Concentrations across Europe. Epidemiology. 2009; 20 ():S64-S65.

Chicago/Turabian Style

Danielle Vienneau; Kees De Hoogh; David Briggs. 2009. "A Novel GIS Method for Modelling 1 km NO2 Concentrations across Europe." Epidemiology 20, no. : S64-S65.

Abstracts
Published: 01 November 2009 in Epidemiology
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ACS Style

John Gulliver; David Briggs. STEMS-Air: A GIS-Based Dispersion Model for City-Wide Exposure Assessment. Epidemiology 2009, 20, S245 .

AMA Style

John Gulliver, David Briggs. STEMS-Air: A GIS-Based Dispersion Model for City-Wide Exposure Assessment. Epidemiology. 2009; 20 ():S245.

Chicago/Turabian Style

John Gulliver; David Briggs. 2009. "STEMS-Air: A GIS-Based Dispersion Model for City-Wide Exposure Assessment." Epidemiology 20, no. : S245.

Comparative study
Published: 01 March 2009 in Science of The Total Environment
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There is a need to understand much more about the geographic variation of air pollutants. This requires the ability to extrapolate from monitoring stations to unsampled locations. The aim was to assess methods to develop accurate and high resolution maps of background air pollution across the EU. We compared the validity of ordinary kriging, universal kriging and regression mapping in developing EU-wide maps of air pollution on a 1 × 1 km resolution. Predictions were made for the year 2001 for nitrogen dioxide (NO2), fine particles < 10 µm (PM10), ozone (O3), sulphur dioxide (SO2) and carbon monoxide (CO) using routine monitoring data in Airbase. Predictor variables from EU-wide databases were land use, road traffic, population density, meteorology, altitude, topography and distance to sea. Models were developed for the global, rural and urban scale separately. The best method to model concentrations was selected on the basis of predefined performance measures (R2, Root Mean Square Error (RMSE)). For NO2, PM10 and O3 universal kriging performed better than regression mapping and ordinary kriging. Validation of the final universal kriging estimates with results from all validation sites gave R2-values and RMSE-values of 0.61 and 6.73 µg/m3 for NO2; 0.45 and 5.19 µg/m3 for PM10; and 0.70 and 7.69 µg/m3 for O3. For SO2 and CO none of the three methods was able to provide a satisfactory prediction. Reasonable prediction models were developed for NO2, PM10 and O3 on an EU-wide scale. Our study illustrates that it is possible to develop detailed maps of background air pollution using EU-wide databases.

ACS Style

Rob Beelen; Gerard Hoek; Edzer Pebesma; Danielle Vienneau; Kees de Hoogh; David J. Briggs. Mapping of background air pollution at a fine spatial scale across the European Union. Science of The Total Environment 2009, 407, 1852 -1867.

AMA Style

Rob Beelen, Gerard Hoek, Edzer Pebesma, Danielle Vienneau, Kees de Hoogh, David J. Briggs. Mapping of background air pollution at a fine spatial scale across the European Union. Science of The Total Environment. 2009; 407 (6):1852-1867.

Chicago/Turabian Style

Rob Beelen; Gerard Hoek; Edzer Pebesma; Danielle Vienneau; Kees de Hoogh; David J. Briggs. 2009. "Mapping of background air pollution at a fine spatial scale across the European Union." Science of The Total Environment 407, no. 6: 1852-1867.

Journal article
Published: 30 November 2008 in Social Science & Medicine
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Recent studies have suggested that more deprived people tend to live in areas characterised by higher levels of environmental pollution. If generally true, these environmental inequities may combine to cause adverse effects on health and also exacerbate problems of confounding in epidemiological studies. Previous studies of environmental inequity have nevertheless indicated considerable complexity in the associations involved, which merit further investigation using more detailed data and more advanced analytical methods. This study investigates the ways in which environmental inequity in England varies in relation to: (a) different environmental pollutants (measured in different ways); (b) different aspects of socio-economic status; and (c) different geographical scales and contexts (urban vs. rural). Associations were analysed between the Index of Multiple Deprivation (IMD2004) and its domains and five sets of environmental pollutants (relating to road traffic, industry, electro-magnetic frequency radiation, disinfection by-products in drinking water and radon), measured in terms of proximity, emission intensity and environmental concentration. Associations were assessed using bivariate and multivariate correlation, and by comparing the highest and lowest quintiles of deprivation using Student's t-test and Hotelling's T2. Associations are generally weak (R2 < 0.10), and vary depending on the specific measures used. Strongest associations occur with what can be regarded as contingent components of deprivation (e.g. crime, living environment, health) rather than causative factors such as income, employment or education. Associations also become stronger with increasing level of spatial aggregation. Overall, the results suggest that any triple jeopardy for health, and problems of confounding, associated with environmental inequities are likely to be limited.

ACS Style

David Briggs; Juan J. Abellan; Daniela Fecht. Environmental inequity in England: Small area associations between socio-economic status and environmental pollution. Social Science & Medicine 2008, 67, 1612 -1629.

AMA Style

David Briggs, Juan J. Abellan, Daniela Fecht. Environmental inequity in England: Small area associations between socio-economic status and environmental pollution. Social Science & Medicine. 2008; 67 (10):1612-1629.

Chicago/Turabian Style

David Briggs; Juan J. Abellan; Daniela Fecht. 2008. "Environmental inequity in England: Small area associations between socio-economic status and environmental pollution." Social Science & Medicine 67, no. 10: 1612-1629.

Review
Published: 27 November 2008 in Environmental Health
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Traditional methods of risk assessment have provided good service in support of policy, mainly in relation to standard setting and regulation of hazardous chemicals or practices. In recent years, however, it has become apparent that many of the risks facing society are systemic in nature – complex risks, set within wider social, economic and environmental contexts. Reflecting this, policy-making too has become more wide-ranging in scope, more collaborative and more precautionary in approach. In order to inform such policies, more integrated methods of assessment are needed. Based on work undertaken in two large EU-funded projects (INTARESE and HEIMTSA), this paper reviews the range of approaches to assessment now in used, proposes a framework for integrated environmental health impact assessment (both as a basis for bringing together and choosing between different methods of assessment, and extending these to more complex problems), and discusses some of the challenges involved in conducting integrated assessments to support policy. Integrated environmental health impact assessment is defined as a means of assessing health-related problems deriving from the environment, and health-related impacts of policies and other interventions that affect the environment, in ways that take account of the complexities, interdependencies and uncertainties of the real world. As such, it depends heavily on how issues are selected and framed, and implies the involvement of stakeholders both in issue-framing and design of the assessment, and to help interpret and evaluate the results. It is also a comparative process, which involves evaluating and comparing different scenarios. It consequently requires the ability to model the way in which the influences of exogenous factors, such as policies or other interventions, feed through the environment to affect health. Major challenges thus arise. Chief amongst these are the difficulties in ensuring effective stakeholder participation, in dealing with the multicausal and non-linear nature of many of the relationships between environment and health, and in taking account of adaptive and behavioural changes that characterise the systems concerned.

ACS Style

David J Briggs. A framework for integrated environmental health impact assessment of systemic risks. Environmental Health 2008, 7, 61 -17.

AMA Style

David J Briggs. A framework for integrated environmental health impact assessment of systemic risks. Environmental Health. 2008; 7 (1):61-17.

Chicago/Turabian Style

David J Briggs. 2008. "A framework for integrated environmental health impact assessment of systemic risks." Environmental Health 7, no. 1: 61-17.

Journal article
Published: 30 October 2008 in Environmental Geochemistry and Health
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Environmental epidemiology and health risk and impact assessment have long grappled with problems of uncertainty in data and their relationships. These uncertainties have become more challenging because of the complex, systemic nature of many of the risks. A clear framework defining and quantifying uncertainty is needed. Three dimensions characterise uncertainty: its nature, its location and its level. In terms of its nature, uncertainty can be both intrinsic and extrinsic. The former reflects the effects of complexity, sparseness and nonlinearity; the latter arises through inadequacies in available observational data, measurement methods, sampling regimes and models. Uncertainty occurs in three locations: conceptualizing the problem, analysis and communicating the results. Most attention has been devoted to characterising and quantifying the analysis--a wide range of statistical methods has been developed to estimate analytical uncertainties and model their propagation through the analysis. In complex systemic risks, larger uncertainties may be associated with conceptualization of the problem and communication of the analytical results, both of which depend on the perspective and viewpoint of the observer. These imply using more participatory approaches to investigation, and more qualitative measures of uncertainty, not only to define uncertainty more inclusively and completely, but also to help those involved better understand the nature of the uncertainties and their practical implications.

ACS Style

David J. Briggs; Clive E. Sabel; Kayoung Lee. Uncertainty in epidemiology and health risk and impact assessment. Environmental Geochemistry and Health 2008, 31, 189 -203.

AMA Style

David J. Briggs, Clive E. Sabel, Kayoung Lee. Uncertainty in epidemiology and health risk and impact assessment. Environmental Geochemistry and Health. 2008; 31 (2):189-203.

Chicago/Turabian Style

David J. Briggs; Clive E. Sabel; Kayoung Lee. 2008. "Uncertainty in epidemiology and health risk and impact assessment." Environmental Geochemistry and Health 31, no. 2: 189-203.

Review
Published: 01 October 2008 in Atmospheric Environment
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ACS Style

Gerard Hoek; Rob Beelen; Kees De Hoogh; Danielle Vienneau; John Gulliver; Paul Fischer; David Briggs. A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmospheric Environment 2008, 42, 7561 -7578.

AMA Style

Gerard Hoek, Rob Beelen, Kees De Hoogh, Danielle Vienneau, John Gulliver, Paul Fischer, David Briggs. A review of land-use regression models to assess spatial variation of outdoor air pollution. Atmospheric Environment. 2008; 42 (33):7561-7578.

Chicago/Turabian Style

Gerard Hoek; Rob Beelen; Kees De Hoogh; Danielle Vienneau; John Gulliver; Paul Fischer; David Briggs. 2008. "A review of land-use regression models to assess spatial variation of outdoor air pollution." Atmospheric Environment 42, no. 33: 7561-7578.

Comparative study
Published: 31 January 2008 in Environment International
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Monitoring was carried out of particulate concentrations whilst simultaneously walking and driving 48 routes in London, UK. Monitoring was undertaken during May and June 2005. Route lengths ranged from 601 to 1351 m, and most routes were travelled in both directions. Individual journey times ranged from 1.5 to 15 min by car (average 3.7 min) and 7.3 to 30 min (average 12.8 min) whilst walking; car trips were therefore repeated up to 5 times for each single walking trip and the results averaged for the route. Car trips were made with windows closed and the ventilation system on a moderate setting. Results show that mean exposures while walking are greatly in excess of those while driving, by a factor 4.7 for the coarse particle mass (PM10–PM2.5), 2.2 for the fine particle mass (PM2.5–PM1), 1.9 for the very fine particle mass (< PM1) and 1.4 for ultrafine particle number density. The reduced in-car exposures appear to occur largely because the filtration system helps to prevent ingress of particles, so that the vehicle acts as a more-or-less independent micro-environment, insulated against much of air pollution present in the street. When account is also taken of the additional travel time involved in walking, these excesses are further increased: to factors of 15.6, 7.4, 6.5 and 4.4, respectively. Individuals who change their travel mode from car to walking in response to policies aimed at encouraging a modal shift in travel behavior are thus likely to experience considerably increased journey-time personal exposures to traffic-related air pollution. More effort is consequently needed to increase separation between road vehicles and pedestrians if negative effects of these policies are to be avoided.

ACS Style

David J. Briggs; Kees de Hoogh; Chloe Morris; John Gulliver. Effects of travel mode on exposures to particulate air pollution. Environment International 2008, 34, 12 -22.

AMA Style

David J. Briggs, Kees de Hoogh, Chloe Morris, John Gulliver. Effects of travel mode on exposures to particulate air pollution. Environment International. 2008; 34 (1):12-22.

Chicago/Turabian Style

David J. Briggs; Kees de Hoogh; Chloe Morris; John Gulliver. 2008. "Effects of travel mode on exposures to particulate air pollution." Environment International 34, no. 1: 12-22.