IDEAS home Printed from https://ideas.repec.org/a/sae/envira/v42y2010i7p1650-1668.html
   My bibliography  Save this article

Developing Summary Measures of Health-Related Multiple Physical Environmental Deprivation for Epidemiological Research

Author

Listed:
  • Elizabeth A Richardson

    (School of GeoSciences, The University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, Scotland)

  • Richard Mitchell

    (Section of Public Health and Health Policy, Faculty of Medicine, University of Glasgow, 1 Lilybank Gardens, Glasgow G12 8RZ, Scotland)

  • Niamh K Shortt
  • Jamie Pearce

    (School of GeoSciences, The University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, Scotland)

  • Terence P Dawson

    (School of Geography, University of Southampton, Highfield, Southampton SO17 1BJ, England)

Abstract

Socioeconomic deprivation accounts for much of the spatial inequality in health in the UK, but a significant proportion remains unexplained. It is highly likely that the physical environment is a key factor in this unexplained variation. The role of the socioeconomic environment in health inequalities has been studied using small-area measures of multiple socioeconomic deprivation that capture the burden of socioeconomic adversity. Although similar composite measures of the physical environment would greatly assist investigations of environmental determinants of health no such measures are available. In this study we developed two small-area measures of health-related multiple physical environmental deprivation for the UK. A thorough review and evidence appraisal process was used to identify health-relevant dimensions of physical environmental deprivation. As a result we selected both health-detrimental (air pollution, cold climate, industrial facilities) and health-beneficial (ultraviolet radiation and green space) dimensions. Datasets describing each of the selected dimensions were acquired, and rendered to UK Census Area Statistics wards ( n = 10 654, average population = 5518). We developed two summary measures: the multiple environmental deprivation index (MEDIx) and classification (MEDClass). MEDIx, on an ordinal scale, can be used to distinguish areas exposed to greater or lesser environmental deprivation. MEDClass groups areas with similar environmental characteristics and will be useful for exploring health effects of specific types of environment. Mapping these measures demonstrated a wide variation in physical environmental deprivation across the UK. MEDIx revealed greater environmental deprivation in urban and industrial areas, and at more northerly latitudes. Although created using a different methodology MEDClass also differentiated these environmental types. We concluded that it is possible to capture and characterise multiple attributes of health-related physical environmental deprivation in the UK, at a small area level. The measures we developed offer opportunities to researchers and policy makers for developing our understanding of the role of exposure to multiple dimensions of physical environmental deprivation on health outcomes.

Suggested Citation

  • Elizabeth A Richardson & Richard Mitchell & Niamh K Shortt & Jamie Pearce & Terence P Dawson, 2010. "Developing Summary Measures of Health-Related Multiple Physical Environmental Deprivation for Epidemiological Research," Environment and Planning A, , vol. 42(7), pages 1650-1668, July.
  • Handle: RePEc:sae:envira:v:42:y:2010:i:7:p:1650-1668
    DOI: 10.1068/a42459
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/a42459
    Download Restriction: no

    File URL: https://libkey.io/10.1068/a42459?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. M. Saisana & A. Saltelli & S. Tarantola, 2005. "Uncertainty and sensitivity analysis techniques as tools for the quality assessment of composite indicators," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 307-323, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tunstall, Helena & Mitchell, Richard & Pearce, Jamie & Shortt, Niamh, 2014. "The general and mental health of movers to more- and less-disadvantaged socio-economic and physical environments within the UK," Social Science & Medicine, Elsevier, vol. 118(C), pages 97-107.
    2. Pearce, Jamie R. & Richardson, Elizabeth A. & Mitchell, Richard J. & Shortt, Niamh K., 2011. "Environmental justice and health: A study of multiple environmental deprivation and geographical inequalities in health in New Zealand," Social Science & Medicine, Elsevier, vol. 73(3), pages 410-420, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Matthias Firgo & Fabian Gabelberger & Andreas Reinstaller & Yvonne Wolfmayr, 2024. "Assessing Regional Production Potential to Strengthen the Security of Supply in Strategic Products," WIFO Working Papers 670, WIFO.
    2. Rajko Tomaš, 2022. "Measurement of the Concentration of Potential Quality of Life in Local Communities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(1), pages 79-109, August.
    3. Janina Isabel Steinert & Lucie Dale Cluver & G. J. Melendez-Torres & Sebastian Vollmer, 2018. "One Size Fits All? The Validity of a Composite Poverty Index Across Urban and Rural Households in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 51-72, February.
    4. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2018. "σ-µ efficiency analysis: A new methodology for evaluating units through composite indices," MPRA Paper 83569, University Library of Munich, Germany.
    5. Marco Marozzi & Mario Bolzan, 2018. "An Index of Household Accessibility to Basic Services: A Study of Italian Regions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(3), pages 1237-1250, April.
    6. Di Zio, Simone & Bolzan, Mario & Marozzi, Marco, 2021. "Classification of Delphi outputs through robust ranking and fuzzy clustering for Delphi-based scenarios," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    7. Drago, Carlo & Gatto, Andrea, 2022. "Policy, regulation effectiveness, and sustainability in the energy sector: A worldwide interval-based composite indicator," Energy Policy, Elsevier, vol. 167(C).
    8. Brad Carter & Claus Rinner, 2014. "Locally weighted linear combination in a vector geographic information system," Journal of Geographical Systems, Springer, vol. 16(3), pages 343-361, July.
    9. Paola Costantini & Marielle Linting & Giovanni C. Porzio, 2010. "Mining performance data through nonlinear PCA with optimal scaling," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 26(1), pages 85-101, January.
    10. Qingyun Du & Yanxia Wang & Fu Ren & Zhiyuan Zhao & Hongqiang Liu & Chao Wu & Langjiao Li & Yiran Shen, 2014. "Measuring and Analysis of Urban Competitiveness of Chinese Provincial Capitals in 2010 under the Constraints of Major Function-Oriented Zoning Utilizing Spatial Analysis," Sustainability, MDPI, vol. 6(6), pages 1-26, May.
    11. Laurens CHERCHYE & Willem MOESEN & Nicky ROGGE & Tom VAN PUYENBROECK, 2009. "Constructing a knowledge economy composite indicator with imprecise data," Working Papers of Department of Economics, Leuven ces09.15, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    12. Rachel M. Gisselquist, 2013. "Evaluating Governance Indexes: Critical and Less Critical Questions," WIDER Working Paper Series wp-2013-068, World Institute for Development Economic Research (UNU-WIDER).
    13. Ludovico Carrino, 2016. "Data Versus Survey-based Normalisation in a Multidimensional Analysis of Social Inclusion," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(3), pages 305-345, November.
    14. Koray Altintas & Ozalp Vayvay & Sinan Apak & Emine Cobanoglu, 2020. "An Extended GRA Method Integrated with Fuzzy AHP to Construct a Multidimensional Index for Ranking Overall Energy Sustainability Performances," Sustainability, MDPI, vol. 12(4), pages 1-21, February.
    15. Edson Kogachi & Adonias Ferreira & Carlos Cavalcante & Marcelo Embiruçu, 2021. "Development of Performance Evaluation Indicators for Table Grape Packaging Units. 2. Global Indexes," Sustainability, MDPI, vol. 13(11), pages 1-16, June.
    16. Raffaele Lagravinese & Paolo Liberati & Giuliano Resce, 2017. "Exploring health outcomes by stochastic multi-objective acceptability analysis: an application to Italian regions," Working Papers. Collection B: Regional and sectoral economics 1703, Universidade de Vigo, GEN - Governance and Economics research Network.
    17. Greco, Salvatore & Ishizaka, Alessio & Tasiou, Menelaos & Torrisi, Gianpiero, 2019. "Sigma-Mu efficiency analysis: A methodology for evaluating units through composite indicators," European Journal of Operational Research, Elsevier, vol. 278(3), pages 942-960.
    18. Riccardo Natoli & Segu Zuhair, 2010. "Establishing the RIE index: a review of the components critical to progress measurement," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 37(8), pages 574-591, July.
    19. Milica Maricic & Milica Kostic-Stankovic, 2016. "Towards an impartial Responsible Competitiveness Index: a twofold multivariate I-distance approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 103-120, January.
    20. Gardó, Sándor & Klaus, Benjamin, 2020. "Overcapacities in banking: Measurement, trends and determinants," Economic Modelling, Elsevier, vol. 91(C), pages 819-834.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:envira:v:42:y:2010:i:7:p:1650-1668. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.