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Show the results of some test for statistically significant differences? If points are used, how will overlapping points be represented? Should the maps be printed in color? The inclusion of physical features, such as highway systems, bodies of water, or other landscape features can serve as landmarks to orient the viewer. In addition to orienting the viewer, roads communicate population density. These are just a few examples of display decisions involved in mapping. For a more detailed discussion of the presentation of maps, refer to Tufte (1983, 1990), and Steinberg (1995). Conclusions Small area analysis has many applications to public health. It can be used to express variation in health services utilization, to identify populations most at need as an aid in targeting health promotions and interventions, and to examine health events and health status in small areas to identify problems. Potential determinants of community health status may be suggested by comparing health status and health events to demographic, environmental and health system attributes. One limitation that can be dealt with but never solved is that small areas are, by definition, small, yielding small population sizes and small numbers of health events. This causes problems for statisticians and decision-makers alike because small numbers produce unstable estimates, which are a poor basis for decisions. However, appropriate statistical methods can help deal with the issue of small numbers. A limitation that is not in the investigator's control is the accuracy of existing data. Small area analysis relies on the accuracy of event and population data. Even U.S. Census Bureau population estimates, commonly assumed by many to be "truth," have error margins and under enumerate certain populations (U.S. Bureau of the Census, 1995), which can be problematic when estimates are applied to small areas. Accuracy issues also apply to vital records, hospital, and survey data. Another complication arising from the size of the populations in small areas is that of individual privacy. Providing information about the health of a black, 24-year-old female who lives somewhere in the U.S. is not intrusive on that individual's privacy, whereas providing that same information on the same person is definitely an intrusion on her privacy if it is disclosed that she lives in Snowville, UT. Whenever the possibility exists of identifying an individual, important ethical concerns about the potential public costs and benefits of storing, using, and reporting information must be addressed. Use of ZIP codes or other area blocks to geocode population sizes and health events is an imperfect approach. ZIP code areas are not based on geographic homogeneity. Using a ZIP code characteristic, such as income, as a proxy for a person's household income introduces misclassification bias, leading to underestimates of statistical relationships (Gould, Davey & LeRoy, 1989). Identifying the exact geographic coordinates of persons and health events would be superior, but this information can be difficult to obtain. Cross references that code street names and addresses into Cartesian coordinates exist, but in growing areas, they quickly become out-of-date. Using these systems also requires that the address data be rigidly standardized, so that "300 South Street" is always written exactly the same way, and not as "3rd So." or any number of other variants. Small area analysis would benefit not only from better geocoding, but also from adopting standard forms for the geocoding of information. These standards would need to be applied not only to health data, but also to demographic, survey, and other data that could be examined with small area analysis. The demand for information at the community level is great and will probably continue to be so. Public health planning at the community level would benefit greatly from having more proximal and detailed information about the health of their communities. In addition, as we accumulate information on small areas, we can examine community health status trends over time. Although there are challenges to performing small area analysis, many of them may be overcome, and when analyzed correctly and presented appropriately the information these techniques provides can be quite valuable. References Ahlbom, A. (1993) Biostatistics for Epidemioligists. Boca Raton: Lewis Publishers. Andrews, H. F., Kerner, J. F., Zauber, A. G., Mandelblatt, J., Pittman, J., & Struening, E. (1994). Using Census and Mortality Data to Target Small Areas for Breast, Colorectal, and Cervical Cancer Screening. American Journal of Public Health, 84,56-61. American Public Health Association (1991) Healthy Communities 2000: Model Standards. Guidelines for Community Attainment of the Year 2000 National Health Objectives. (3rd Ed.) 25 |
