Spatial Analysis of Disease — Applications

  • B. Sue Bell
Part of the Cancer Treatment and Research book series (CTAR, volume 113)


The objective of this chapter is to provide useful information for taking the spatial analysis of health data “from the lab to the clinic.” The preceding chapter reviewed the history and theory of spatial statistics as applied to health data. This chapter provides examples of how this theory can be used in practice. Emphasis is placed on the tools and resources available to enable a statistical analyst to perform a spatial statistical analysis. Because the methods and software are constantly improving, the author advises the reader to review the latest literature as a first step in embarking on a spatial analysis.


Geographic Information System Spatial Analysis Census Tract Areal Unit Geographic Information System Software 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Armstrong M. P., Rushton G., Zimmerman D. L. (1999). Geographically masking health data to preserve confidentiality. Statistics in Medicine 18 (5): 497–525.PubMedCrossRefGoogle Scholar
  2. Besag J. (1974). Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society, Series B 36: 192–236.Google Scholar
  3. Besag J., York J., Mollie A. (1991). Bayesian image restoration with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics 43 (1): 1–59.CrossRefGoogle Scholar
  4. Breslow N. E., Clayton D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88 (421): 9–25.Google Scholar
  5. Maptitude® Geographic Information System for Windows (2000). Version 4.2. Newton, MA:Google Scholar
  6. Clayton D., Bernardinelli L. (1992). Bayesian methods for mapping disease risk. In: Elliott P., Cuzick J., English D., Stern R., editors. Geographical and Environmental Epidemiology: Methods for Small Area Studies. New York: Oxford University Press; p 205–20.Google Scholar
  7. Clayton D., Kaldor J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics 43: 671–81.PubMedCrossRefGoogle Scholar
  8. Cressie N. A. C. (1993). Statistics for Spatial Data. Revised ed. New York: J. Wiley.Google Scholar
  9. Cressie N. A. C., Chan N. H. (1989). Spatial modeling of regional variables. Journal of the American Statistical Association 84 (406): 393–401.CrossRefGoogle Scholar
  10. Cressie N. A. C., Read T. R. C. (1989). Spatial data-analysis of regional counts. Biometrical Journal 31 (6): 699–719.CrossRefGoogle Scholar
  11. Department of Health and Human Services. (1999). Standards for privacy of individually identifiable health information. Office of the Assistant Secretary for Planning and Evaluation, DHHS. Proposed rule. Federal Register 64 (212): 59918–60065.Google Scholar
  12. Devesa S., Grauman D. J., Blot W. J., Pennello G. A., Hoover R. N., Fraumeni Jr J. F. (1999). Atlas of Cancer Mortality in the United States: 1950–94. Bethesda, MD: National Cancer Institute.Google Scholar
  13. ArcView Spatial Analyst (2000). Version 2. 0a. Redlands, CA: Environmental Systems Research Institute, Inc.Google Scholar
  14. Frisbie W. P., Biegler M., de Turk P., Forbes D., Pullum S. G. (1997). Racial and ethnic differences in determinants of intrauterine growth retardation and other compromised birth outcomes. American Journal of Public Health 87 (12): 1977–83.PubMedCrossRefGoogle Scholar
  15. Goldstein H., Rasbash J. (1996). Improved approximations for multilevel models with binary responses. Journal of the Royal Statistical Society, Series A 159: 505–13.Google Scholar
  16. Kaluzny S. P., Vega S. C., Cardoso T. P., Shelly A. A. (1998). S+ Spatial Stats: User’s manual for Windows ® and UNLY®. New York: Springer.Google Scholar
  17. Haining R. P. (1990). Spatial Data Analysis in the Social and Environmental Sciences. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  18. Kulldorff M. (1997). A spatial scan statistic. Communications in Statistics-Theory and Methods 26: 1481–96.CrossRefGoogle Scholar
  19. Kulldorff M., Nagarwalla N. (1995). Spatial disease clusters: detection and inference. Statistics in Medicine 14 (8): 799–810.PubMedCrossRefGoogle Scholar
  20. Littell R. C., Milliken G. A., Stroup W. W., Wolfinger R. D. (1996). SAS ® System for Mixed Models. Cary, NC: SAS Institute Inc.Google Scholar
  21. Manton K. G., Woodbury M. A., Stallard E., Riggan W. B., Creason J. P., Pellom A. C. (1989). Empirical Bayes procedures for stabilizing maps of U.S.cancer mortality rates. Journal of the American Statistical Association 84: 637–50.PubMedCrossRefGoogle Scholar
  22. Mapinfo Professional® (2000). Troy, NY: Mapinfo CorporationGoogle Scholar
  23. Meade M. S., Florin J. W., Gesler W. M. (1988). Medical Geography. New York: Guilford Press.Google Scholar
  24. O’Campo P., Xue X., Wang M. C., Caughy M. (1997). Neighborhood risk factors for low birthweight in Baltimore: a multilevel analysis. American Journal of Public Health 87 (7): 1113–8.PubMedCrossRefGoogle Scholar
  25. Pickle L. W., Mungiole M., Jones G. K., White A. A. (1996). Atlas of United States Mortality. Hyattsville, MD: National Center for Health Statistics.Google Scholar
  26. Pickle L. W., White A. A. (1995). Effects of the choice of age-adjustment method on maps of death rates. Statistics in Medicine 14 (5–7): 615–27.PubMedCrossRefGoogle Scholar
  27. Rasbash J., Browne W., Goldstein H., Yang M., Plewis I., Healy M., Woodhouse G., Draper D., Langford I., Lewis T. (2000). A User’s Guide to MLwiN. London: Multilevel Models Project, Institute of Education, University of London.Google Scholar
  28. Raudenbush S. W., Yang M. L., Yosef M. (2000). Maximum likelihood for generalized linear models with nested random effects via high-order, multivariate Laplace approximation. Journal of Computational and Graphical Statistics 9 (1): 141–57.Google Scholar
  29. Rushton G., Krishnamurthy R., Krishnamurti D., Lolonis P., Song H. (1996). The spatial relationship between infant mortality and birth defect rates in a U.S. city. Statistics in Medicine 15 (17–18): 1907–19.PubMedCrossRefGoogle Scholar
  30. Rushton G., Lolonis P. (1996). Exploratory spatial analysis of birth defect rates in an urban population. Statistics in Medicine 15 (7–9): 717–26.PubMedCrossRefGoogle Scholar
  31. Showstack J. A., Budetti P. P., Minkler D. (1984). Factors associated with birthweight: an exploration of the roles of prenatal care and length of gestation. American Journal of Public Health 74 (9): 1003–8.PubMedCrossRefGoogle Scholar
  32. Snijders T. A. B., Bosker R. J. (1999). Multilevel Analysis: An introduction to basic and advanced multilevel modeling. London: Sage Publications.Google Scholar
  33. Spiegelhalter D., Thomas A., Best N., Gilks W. (1995). BUGS: Bayesian inference using GIBBS Sampling, Version 0.50. Cambridge: MRC Biostatistics Unit.Google Scholar
  34. Spiegelhalter D., Thomas A., Best N., Gilks W. (1996). BUGS 0.5* Examples Volume 2 (version ii). Cambridge: MRC Biostatistics Unit, Institute of Public Health.Google Scholar
  35. Stehman S. V., Overton W. S. (1996). Spatial Sampling. In: Arlinghaus S. L., editor. Practical Handbook of Spatial Statistics. New York: CRC Press; p 31–63.Google Scholar
  36. Usher R., McLean F. (1969). Intrauterine growth of live-born Caucasian infants at sea level: standards obtained from measurements in 7 dimensions of infants born between 25 and 44 weeks of gestation. Journal of Pediatrics 74 (6): 901–10.PubMedCrossRefGoogle Scholar
  37. Waller L. A., Carlin B. P., Xia H., Gelfand A. E. (1997). Hierarchical spatiotemporal mapping of disease rates. Journal of the American Statistical Association 92 (438): 607–17.CrossRefGoogle Scholar
  38. Xia H., Carlin B. P. (1998). Spatio-temporal models with errors in covariates: mapping Ohio lung cancer mortality. Statistics in Medicine 17 (18): 2025–43.PubMedCrossRefGoogle Scholar
  39. Zakos-Feliberti A. 2000. [Personal Communication to B.Sue Bell].Google Scholar

Copyright information

© Springer Science+Business Media New York 2002

Authors and Affiliations

  • B. Sue Bell
    • 1
  1. 1.National Cancer InstituteUSA

Personalised recommendations