Presentation on theme: "Part 1: Developing MEDIx and MEDClass Richard Mitchell (PI), Niamh Shortt, Jamie Pearce, Elizabeth Richardson, Terry Dawson."— Presentation transcript:
Part 1: Developing MEDIx and MEDClass Richard Mitchell (PI), Niamh Shortt, Jamie Pearce, Elizabeth Richardson, Terry Dawson
Funding NERC Environment and Human Health programme Supported by: NERC EA Defra MOD MRC The Wellcome Trust ESRC BBSRC EPSRC HPA
Exploratory award: Multiple environmental classification of areas for researching health inequality Objectives: 1)To develop a measure of health-related multiple physical environmental deprivation for the UK (small-area level) 1)To determine its utility in researching spatial inequalities in health
Outline Objective 1: To develop a measure of health-related multiple physical environmental deprivation for the UK (small-area level) WHY? HOW? Over-arching principles Identification of health-relevant dimensions of environmental deprivation Dataset acquisition and processing Construction of the summary measures: Index Classification
Spatial health inequalities Widening spatial inequalities in health Why? Standardised mortality rate 1999-2003 150 70 100
Spatial health inequalities Socioeconomic deprivation ‘explains’ much: But, significant proportion remains unexplained… … role of the physical environment? How would we investigate this? How would we measure ‘the physical environment’? Increasing affluence Increasing life expectancy Britain, males and females; Drawn from data in Shaw et al. (2005) Why?
Measures of Multiple Socioeconomic Deprivation: Carstairs score Indices of Multiple Deprivation Socioeconomic deprivation Socioeconomic deprivation: Multi-dimensional, e.g.: Poverty Housing conditions Material possessions Employment Why?
Measures of Multiple Physical Environmental Deprivation? Environmental deprivation Physical environmental deprivation: Multi-dimensional, e.g.: Air pollution Climate Radiation Greenspace Why?
Over-arching principles Health-relevant Scientifically credible User-friendly and useful Repeatable (Briggs, 2000; Corvalán et al., 2000; Nardo et al., 2008; Sol et al., 1995) How?
Development stages 1. Identify health-relevant dimensions of physical environmental deprivation 2. Identify and acquire datasets 3. Render to same geography 5. Test for associations with health outcomes 4. Develop summary measures How?
Identify dimensions of environmental deprivation 1.Scoping review Grey literature Reference databases Long list 2.Systematic literature search Appraisal of health-relevance: Methodological rigour Strength of association with health Prevalence of health outcome > 10% UK population exposure ‘ Wish list’ How? Air pollutants Climate (temperature) Solar UV radiation Greenspace Industrial facilities Drinking water quality Noise ELF radiation (power lines) RF radiation (transmitters) Radon Individual industrial pollutants Nuclear facilities Contaminated land Food environment Accidents
Evidence for wish-listed factors How? Wish list dimensions Detrimental? Beneficial? Air pollutants Climate (temperature) Solar UV radiation Greenspace Certain industrial facilities Drinking water quality Noise
Dataset acquisition and processing How? Wish list dimensions Air pollutants National Atmospheric Emissions Inventory (NAEI) 1 km grids Climate (temperature) Met Office, 5 km grids Solar UV radiation UVB Index (Mo & Green, 1974) calculated from Met Office cloud cover data & latitude Greenspace Generalised Land Use Database (GLUD) CORINE Land Cover Data (modelled %) Industrial facilities European Pollutant Emission Register (EPER); facility type and grid ref Drinking water quality Noise
Summary of environmental data How? Geography = UK CAS wards: n = 10,654 (in 2001) Average population ~5,500 Detrimental factors: Air pollutants Proximity to industry Cold climate Beneficial factors: Solar UV radiation Greenspace availability
Cold, Clean and Green Alternative summary measures How? 1. An index a scale or ranking increasing value reflects increasing environmental ‘burden’ 2. A classification a label or category groups areas that share the same specific types of environment Complementary uses: Dose-response effect? Health consequences of specific combinations of environments?
Constructing the index How? Aim: To represent relative ‘level’ of health- related environmental deprivation To reflect both detrimental and beneficial environments Unambiguous and easy to interpret
How to identify better or worse environments? A range of options… simplicity guided our choice: 1.Identify wards exposed to each environmental factor at a ‘detrimental’ (or ‘beneficial’) level 2.Index = balance of number of detrimental to number of beneficial exposures experienced by each ward Constructing the index How?
Constructing the index How? Effect thresholds? Arbitrary decision: ‘health-relevant’ level = highest exposure quintile (i.e., most exposed 20% of wards in the UK) Increasing PM10 No. of wards ‘health-relevant’ exposure 12345
Calculation for each ward: Detrimental exposures:Score Highest air pollution (any pollutant)?+1 or 0 Highest proximity to industry?+1 or 0 Coldest temperatures?+1 or 0 Beneficial exposures: Highest greenspace availability?-1 or 0 Highest UV levels?-1 or 0 Multiple Environmental Deprivation Index (MEDIx) -2 to +3 Constructing the index How?
Constructing the index III e.g. Rotherhithe, East End of London: Detrimental exposures:Score Highest air pollution?+1 Highest proximity to industry?+1 Coldest temperatures?0 Beneficial exposures: Highest greenspace availability?0 Highest UV levels?0 MEDIx+2 How?
Multiple Environmental Deprivation Index (MEDIx) How? MEDIx score -2 = Least environmentally deprived wards (‘healthiest’ places, theoretically) MEDIx score +3 = Most environmentally deprived wards (‘unhealthiest’ places)
Cold, Clean and Green Constructing the classification How?Aim: Identify specific types of health- relevant environment Group wards that share these environmental characteristics
Constructing the classification How? Environmental dimensions Air pollutants Climate (temperature) Solar UV radiation Greenspace Certain industrial facilities Data reduction (PCA) Two-step classification Evaluate solutions Classification
Multiple Environmental Deprivation Classification (MEDClass) How? Clusters = distinct ‘types’ of environment Wards in cluster 7: most greenspace high UV levels low air pollutant levels
Conclusion Yes, it is possible to construct summary measures of multiple environmental deprivation. Rigorous, well-documented process Limitations, room for improvement… Arbitrary decisions Data limitations Part 2: Testing the utility of MEDIx and MEDClass…
References Briggs D, 2000, "Methods for building environmental health indicators", in Decision- making in environmental health Eds C Corvalán, D Briggs, G Zielhuis (E & FN Spon, London) pp 57-76 Corvalán C, Briggs D, Kjellström T, 2000, "The need for information: environmental health indicators", in Decision-making in environmental health Eds C Corvalán, D Briggs, G Zielhuis (E & FN Spon, London) pp 25-56 Nardo M, Saisana M, Saltelli A, Tarantola S, Hoffman A, Giovannini E, 2008 Handbook on constructing composite indicators: Methodology and user guide. EC Joint Research Centre & OECD Statistics Directorate and the Directorate for Science, Technology and Industry (OECD Publishing, Paris) Mo T, Green AES: A climatology of solar erythema dose. Photochem Photobiol 1974, 20:483-496. Shaw M, Davey Smith G, Dorling D, 2005, "Health inequalities and New Labour: how the promises compare with real progress" BMJ 330 1016-1021 Sol V M, Lammers P E M, Aiking H, de Boer J, Feenstra J F, 1995, "Integrated environmental index for application in land-use zoning" Environmental Management 19 457-467