Journal of Geographical Systems

, Volume 13, Issue 2, pp 173–192 | Cite as

Geodemographics as a tool for targeting neighbourhoods in public health campaigns

  • Jakob Petersen
  • Maurizio Gibin
  • Paul LongleyEmail author
  • Pablo Mateos
  • Philip Atkinson
  • David Ashby
Original Article


Geodemographics offers the prospects of integrating, modelling and mapping health care needs and other health indicators that are useful for targeting neighbourhoods in public health campaigns. Yet reports about this application domain has to date been sporadic. The purpose of this paper is to examine the potential of a bespoke geodemographic system for neighbourhood targeting in an inner city public health authority, Southwark Primary Care Trust, London. This system, the London Output Area Classification (LOAC), is compared to six other geodemographic systems from both governmental and commercial sources. The paper proposes two new indicators for assessing the performance of geodemographic systems for neighbourhood targeting based on local hospital demand data. The paper also analyses and discusses the utility of age- and sex standardisation of geodemographic profiles of health care demand.


Geodemographics Neighbourhood targeting Public health Hospital episode statistics 

JEL Classification

I18 N30 


  1. Batty M (2006) Rank clocks. Nature 444:592–596CrossRefGoogle Scholar
  2. Bleich S, Cutler D, Murray C, Adams A (2008) Why Is the developed world obese? Ann Rev Public Health 29:273–295CrossRefGoogle Scholar
  3. Bodenheimer T, Wagner H, Grumbach K (2002) Improving primary care for patients with chronic illness: the chronic care model, Part 2. JAMA 288(15):1909–1914CrossRefGoogle Scholar
  4. Callingham M (2006) Exploring the use and value of the ONS output area classification. Accessed 3 April 2009
  5. Department of Health (2004a) Choosing health: making healthier choices easier. Department of Health, LondonGoogle Scholar
  6. Department of Health (2004b) Improving chronic disease management. Department of Health, LondonGoogle Scholar
  7. Department of Health (2005) National service framework for long-term conditions. Department of Health, LondonGoogle Scholar
  8. Harris R, Sleight P, Webber R (2005) Geodemographics, GIS and neighbourhood targeting. Wiley, ChichesterGoogle Scholar
  9. Besley T, Kanbur, R (1990) The principles of targeting. Policy Res Working Paper Series 385Google Scholar
  10. Kirkwood BR, Sterne JAC (2003) Essential medical statistics, 2nd edn. Blackwell, MaldenGoogle Scholar
  11. Kotler P, Zaltman G (1971) Social marketing: an approach to planned social change. J Mark 35(3):3–12CrossRefGoogle Scholar
  12. Kotler P, Roberto N, Lee N (2002) Social marketing: improving the quality of life. SAGE, LondonGoogle Scholar
  13. Longley P (2005) A renaissance of geodemographics for public service delivery. Prog Hum Geogr 29(1):57–63CrossRefGoogle Scholar
  14. Noble M, Wright G, Dibben C, Smith G, McLennan D, Anttila C, Barnes H (2004) Indices of Deprivation 2004. Office of the Deputy Prime Minister, LondonGoogle Scholar
  15. Office for National Statistics (2005) All fields postcode directory. LondonGoogle Scholar
  16. Office for National Statistics (1998) Key health statistics from general practice 1998. Analyses of morbidity and treatment data, including time trends, England and Wales. Office for National Statistics, LondonGoogle Scholar
  17. Openshaw S (1984) The modifiable areal unit problem. Concepts and techniques in modern geography. Geo Books, LondonGoogle Scholar
  18. Openshaw S (1995) Geodemographic segmentation systems for screening health data. J Epidemiol Community Health 49:S34–S38CrossRefGoogle Scholar
  19. Rabe-Hesketh S, Everitt B (2004) A handbook of statistical analyses using Stata. Chapman & Hall, CRC, Boca RatonGoogle Scholar
  20. Saxena S, George J, Barber J, Fitzpatrick J, Majeed A (2006) Association of population and practice factors with potentially avoidable admission rates for chronic diseases in London: cross sectional analysis. J R Soc Med 99(2):81–89CrossRefGoogle Scholar
  21. Singleton A, Longley P (2008) Creating open source geodemographics–refining a national classification of Census Output Areas for applications in higher education. Pap Reg Sci 88(3):643–666CrossRefGoogle Scholar
  22. Sleight P (2004) Targeting customers. How to use geodemographics and lifestyle data in your business. WARC, Henley-on-ThamesGoogle Scholar
  23. Speller V, Hale D (1985) Making the most of your postcode. Health Serv J 28:53Google Scholar
  24. Talbot-Smith A, Pollock AM (2006) The new NHS—a guide. Routledge, LondonGoogle Scholar
  25. Vickers D, Birkin M (2007) Creating the UK National Statistics 2001 output areas classification. J R Stat Soc 170(2):379–403CrossRefGoogle Scholar
  26. Wagner H (1998) Chronic disease management: what will it take to improve care for chronic illness? Eff Clin Pract 1(1):2–4Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • Jakob Petersen
    • 1
    • 2
  • Maurizio Gibin
    • 2
    • 3
  • Paul Longley
    • 1
    Email author
  • Pablo Mateos
    • 1
  • Philip Atkinson
    • 2
  • David Ashby
    • 4
  1. 1.Department of Geography and Centre for Advanced Spatial AnalysisUniversity College LondonBloomsburyUK
  2. 2.Southwark Primary Care Trust LondonUK
  3. 3.School of Geography BirkbeckUniversity of LondonLondonUK
  4. 4.Dr Foster (Research) Ltd.LondonUK

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